Ecommerce storefront marketing channel synchronization management

ABSTRACT

Methods and systems for synchronizing product information with one or more channels may include a synchronization engine that may receive, for each storefront of a plurality of storefronts, product information for products and selected channels for the products. The synchronization engine may translate, for each selected channel, relevant product information to a translated product format for each respective selected channel and determine error data relating to the translated product formats. An analysis of error data may be performed, with a recommendation for preventing future synchronization errors for one or more storefronts with a particular channel based on the analysis.

FIELD

The present disclosure relates generally to an e-commerce platform formanaging online and physical stores, and more specifically to asynchronization engine that controls synchronization of productinformation to various advertising and marketing channels.

BACKGROUND

A merchant looking to market and sell products may want to make productinformation available to potential buyers via many different marketingchannels. Each channel may have requirements for product data specificto that channel, such as requirements relating to certain product datafields, e.g., a product ID number, a product price, a category ofproduct, a product image, an availability of the product, and the like.It can be very time consuming for a merchant to provide appropriateproduct information in a suitable format for all the different channels.Past attempts to automate this process have suffered from stress beingplaced on the repositories containing the product information, such asdue to separate synchronizations being required for each channel andpressure on the merchant to resolve any synchronization errors generatedby the various channels. There is therefore a need for a morestreamlined approach to synchronize product information acrossstorefronts and across channels and to address the various errorsencountered as the product information is shared to the differentchannels.

SUMMARY

In embodiments, a method may include receiving, by a synchronizationengine, for at least one storefront, product information for at leastone product and at least one selected channel for the at least oneproduct. The synchronization engine may translate, for the at least onestorefront, relevant product information to a translated product formatfor the at least one selected channel and may determine error datarelating to the translated product format, wherein the error dataincludes at least one of an identified error in the translated productformat and a corresponding way the identified error is resolved. Ananalysis of the error data may be performed, and the synchronizationengine may determine a recommendation for preventing a future errorsynchronizing product data for a first storefront with a particularchannel based on the analysis.

In embodiments, errors may be consolidated across at least two channelsprior to a reporting of identified errors to the at least onestorefront. A predictive analytics module may be used to determine howat least one identified error is resolved. A predictive analytics modulemay be used to determine the recommendation and the recommendation iscommunicated to the at least one storefront for approval prior toimplementation. A predictive analytics module may be used to determinethe recommendation and the recommendation may be automaticallyimplemented. The recommendation may be based on error data across agroup of storefronts for a particular channel. At least one productinformation field may be automatically updated for a storefront notincluded in the group of storefronts based on the analysis of errordata. The synchronization engine may use a synchronization data modelfor translating the product information. The synchronization data modelmay include product data fields required for each channel supported bythe synchronization engine.

In embodiments, a system may include a synchronization engine configuredto store a set of instructions that, when executed cause thesynchronization engine to receive product information for at least oneproduct for a storefront and at least one selected channel for the atleast one product from a commerce management engine, translate theproduct information to a translated product format for the at least oneselected channel, determine at least one error relating to thetranslated product format, and determine a recommendation for preventinga future error synchronizing product data for the storefront with aparticular channel based on an analysis of the at least one error.

In embodiments, the system may include a predictive analytics modulethat is adapted to generate a suggestion to resolve the at least oneerror, wherein the suggestion may be communicated to the storefront forapproval prior to implementation. A recommendation may be determinedusing a predictive analytics module to generate a suggestion to resolvean error, wherein the suggestion may be automatically implemented. Arecommendation may be determined using an analysis of errors across agroup of storefronts for a particular channel. At least one productinformation field may be updated based on the analysis of errors for astorefront not included in the group of storefronts.

In embodiments, a method may include performing an analysis of errordata, by a synchronization engine, wherein the error data includes atleast one identified error from a prior synchronization of productinformation to at least one channel and a corresponding way the at leastone identified error is resolved. The synchronization engine maydetermine a recommendation for preventing a future error synchronizingproduct data for a storefront with a particular channel based on theanalysis.

In embodiments, a predictive analytics module may be used to determinethe recommendation and the recommendation is automatically implemented.The recommendation may be based on error data across a group ofstorefronts for a particular channel. At least one product informationfield may be automatically updated for a storefront not included in thegroup of storefronts based on the analysis of error data. Thesynchronization engine may use a synchronization data model fortranslating the product information. The synchronization data model mayinclude product data fields required for each channel supported by thesynchronization engine.

In embodiments, a system may include a synchronization engine configuredto store a set of instructions that, when executed, cause thesynchronization engine to estimate, using error data, at least onefuture synchronization error of product information to one or morechannels. Each channel may have one or more respective product datafields for that channel and the error data relates to a priorsynchronization of product information from one or more storefronts tothe one or more channels and includes at least one of an identifiederror from the prior synchronization and a corresponding correction forresolving the identified error. The set of instructions, when executed,may cause the synchronization engine to send a request to a commercemanagement engine associated with the one or more storefronts, whereinthe request requests product information for one or more products of theone or more storefronts for a future product synchronization with theone or more channels and includes a request parameter that is based onthe at least one estimated future synchronization error.

In embodiments, the request parameter may be a timing parameter that isbased on a predicted time of resolution of the at least one estimatedfuture synchronization error. The request parameter may be a timingparameter that includes a specified time period for reporting productinformation changes for the one or more products of the one or morestorefronts which occur in the specified time period. The requestparameter may be a timing parameter that includes one or more specifiedtimes for reporting product information changes relative to a priorreporting time for the one or more products of the one or morestorefronts. The request parameter may include at least one productfield of the one or more storefronts. The synchronization engine may beadapted to determine if the one or more channels have any new productdata fields required for synchronization. The synchronization engine maybe adapted to generate a suggestion to provide relevant product data fora new required product data field, wherein the suggestion may beautomatically implemented. The synchronization engine may be adapted toanalyze error data across a group of storefronts or a group of productsfor a particular channel. The synchronization engine may be adapted toanalyze error data on a per channel basis to determine a number ofestimated future errors per channel. The future product synchronizationmay be delayed for a specific channel if the number of future errors forthe channel is greater than a respective predetermined threshold. Thesynchronization engine may be adapted to analyze one or more additionalfactors to determine the request parameter, wherein the one or moreadditional factors include a criticality of the errors, a current loadon a computing resource of the commerce management engine, and apredicted additional load on the commerce management engine based on arequest for a specified amount of product information. Thesynchronization engine, in order to acquire the error data, may beadapted to: receive, for one or more storefronts, product informationfor products and selected channels for the products, translate, for theone or more storefronts, relevant product information to a translatedproduct format for each respective selected channel, and synchronizeeach translated product format with the respective selected channel.

In embodiments, a method may include estimating, by a synchronizationengine using error data, at least one future synchronization error ofproduct information to one or more channels, wherein each channel hasrespective product data fields for that channel, wherein the error datarelates to a prior synchronization of product information from one ormore storefronts to the one or more channels and includes at least oneof an identified error from the prior synchronization and acorresponding correction for resolving the identified error. The methodmay include determining, by the synchronization engine, a load on acomputing resource of a commerce management engine associated with theone or more storefronts, wherein the determined load encompasses atleast one of a current load and a predicted future load on the computingresource of the commerce management engine, and formulating, by thesynchronization engine, a request to the commerce management engine forproduct information for one or more products of the one or morestorefronts for a future synchronization with the one or more channels,wherein the request includes a request parameter that is based on theestimated at least one future synchronization error and the determinedload.

In embodiments, the computing resource may include at least one of anetwork resource, a processing resource, a database resource, a storageresource, and a memory resource. The determined load may comprise acomposite load value. A request may be delayed if the composite loadvalue is above a predetermined level. The predetermined level may varybased on a number of future synchronization errors. The determining andformulating steps may be performed in an iterative manner. An amount ofproduct information requested by the request may be decreased if thecomposite load value is above a predetermined level. A predicted futureload on the computing resource of the commerce management engine may bedue to at least one of a request for a specified amount of productinformation or a request for a specified computation.

In embodiments, a method may include estimating, by a synchronizationengine using error data, at least one future synchronization error ofproduct information to a plurality of channels. Each channel may haverespective product data fields for that channel and the error data mayrelate to a prior synchronization of product information from one ormore storefronts to the plurality of channels and may include at leastone of an identified error from the prior synchronization and acorresponding correction for resolving the identified error. The methodmay include determining whether each channel of the plurality ofchannels is affected by the at least one future synchronization error toa predetermined extent and delaying a future synchronization of productinformation to the plurality of channels if a number of channelsaffected to the predetermined extent is above a predetermined threshold.

In embodiments, each future synchronization error may be categorizedbased on a type of error. Each future synchronization error may bedetermined on a per channel basis and a future synchronization ofproduct information to a specific channel is delayed if the specificchannel is affected to the predetermined extent. The predeterminedextent may relate to a number or a type of future synchronizationerrors. The future synchronization may be delayed for all the channelsof the plurality of channels.

In embodiments, a method may include receiving, by a synchronizationengine, for each storefront of a plurality of storefronts, productinformation for products and selected channels for the products. Thesynchronization engine may translate, for each storefront, relevantproduct information to a translated product format for each respectiveselected channel and may determine error data relating to the translatedproduct formats. The error data may include identified errors in thetranslated product formats and corresponding ways the identified errorsare resolved. An analysis of the error data may be performed and thesynchronization engine may determine a recommendation for preventing afuture error synchronizing product data for a first storefront with aparticular channel based on the analysis.

In embodiments, the synchronization engine may send a communicationincluding the recommendation to the first storefront. The communicationmay comprise a request for updated product information based on therecommendation. Identified errors may be reported to affected ones ofthe plurality of storefronts. Errors may be consolidated across at leasttwo channels prior to a reporting of identified errors to affected onesof the plurality of storefronts. A predictive analytics module may beused to determine at least some of the corresponding ways the identifiederrors are resolved. The predictive analytics module may be used todetermine the recommendation and the recommendation may be communicatedto one or more of the plurality of the storefronts for approval prior toimplementation. The predictive analytics module may be used to determinethe recommendation and the recommendation may be automaticallyimplemented. The recommendation may be based on error data across agroup of storefronts for a particular channel. At least one productinformation field may be automatically updated for a storefront notincluded in the group of storefronts based on the analysis of errordata. The first storefront may select the particular channel forcorresponding products after the analysis of errors occurs based on theanalysis of errors. A particular field of product information may berequested from the first storefront. The synchronization engine may usea synchronization data model for translating the product information.The synchronization data model may include product data fields requiredfor each channel supported by the synchronization engine. Thesynchronization data model may be updated in real time. Thesynchronization data model may be updated based at least in part onautomatic identification of changes in requirements across channels.

In embodiments, a method may include receiving, by a synchronizationengine, product information for products and selected channels for theproducts for a storefront. The synchronization engine may translate, foreach selected channel, the product information to a translated productformat for the selected channel. The synchronization engine maydetermine any errors relating to the translated product formats and maydetermine a recommendation for preventing a future error synchronizingproduct data for the storefront with a particular channel based on ananalysis of any errors.

In embodiments, the synchronization engine may send a communication tothe storefront to request updated product information based on therecommendation. A recommendation may use a predictive analytics moduleto generate a suggestion to resolve an error, wherein the suggestion maybe communicated to the storefront for approval prior to implementation.Determining a recommendation may use a predictive analytics module togenerate a suggestion to resolve an error, wherein the suggestion may beautomatically implemented. Determining a recommendation may include ananalysis of errors across a group of storefronts for a particularchannel. At least one product information field may be updated based onthe analysis of errors for a storefront not included in the group ofstorefronts. The synchronization engine may store received product dataas a synchronization data model. The synchronization data model mayinclude fields for requirements of each channel supported by thesynchronization engine. The synchronization data model may be updated inreal time. The synchronization data model may be updated based onautomatic identification of changes in requirements across channels.

In embodiments, a method may include performing an analysis of errordata, wherein the error data may include identified errors from a priorsynchronization, by a synchronization engine, of product information toat least one channel and corresponding ways the identified errors areresolved. The synchronization engine may determine a recommendation forpreventing a future error synchronizing product data for a storefrontwith a particular channel based on the analysis.

In embodiments, the synchronization engine may send a communicationincluding the recommendation to the storefront. The communication maycomprise a request for updated product information based on therecommendation. A predictive analytics module may be used to determinethe recommendation and the recommendation may be communicated to thestorefront for approval prior to implementation. A predictive analyticsmodule may be used to determine the recommendation and therecommendation may be automatically implemented. The recommendation maybe based on error data across a group of storefronts for a particularchannel. At least one product information field may be automaticallyupdated for a storefront not included in the group of storefronts basedon the analysis of error data. The synchronization engine may use asynchronization data model for translating the product information. Thesynchronization data model may include product data fields required foreach channel supported by the synchronization engine. Thesynchronization data model may be updated in real time.

In embodiments, a system may include a synchronization engine that isadapted to receive, for each storefront of a plurality of storefronts,product information for products and selected channels for the products,translate relevant product information to a translated product formatfor each respective selected channel, determine error data relating tothe translated product formats, wherein the error data may includeidentified errors in the translated product formats and correspondingways the identified errors are resolved. The synchronization engine maybe adapted to perform an analysis of the error data and determine arecommendation for preventing a future error synchronizing product datafor a first storefront with a particular channel based on the analysis.

In embodiments, the synchronization engine may be adapted to send acommunication including the recommendation to the first storefront. Thecommunication may comprise a request for updated product informationbased on the recommendation. The synchronization engine may be adaptedto report identified errors to affected ones of the plurality ofstorefronts. Errors may be consolidated across at least two channelsprior to a reporting of identified errors to affected ones of theplurality of storefronts. A predictive analytics module may be used todetermine at least some of the corresponding ways the identified errorsare resolved. A predictive analytics module may be used to determine therecommendation and the recommendation may be communicated to one or moreof the plurality of the storefronts for approval prior toimplementation. A predictive analytics module may be used to determinethe recommendation and the recommendation may be automaticallyimplemented. The recommendation may be based on error data across agroup of storefronts for a particular channel. At least one productinformation field may be automatically updated for a storefront notincluded in the group of storefronts based on the analysis of errordata. The first storefront may select the particular channel forcorresponding products after the analysis of errors occurs based on theanalysis of errors. A particular field of product information may berequested from the first storefront. The synchronization engine may usea synchronization data model for translating the product information.The synchronization data model may include product data fields requiredfor each channel supported by the synchronization engine. Thesynchronization data model may be updated in real time. Thesynchronization data model may be updated based at least in part onautomatic identification of changes in requirements across channels.

In embodiments, a system may include a synchronization engine that isadapted to receive product information for products and selectedchannels for the products for a storefront, translate, for each selectedchannel, the product information to a translated product format for theselected channel, determine any errors relating to the translatedproduct formats, and determine, by the synchronization engine, arecommendation for preventing a future error synchronizing product datafor the storefront with a particular channel based on an analysis of anyerrors.

In embodiments, the synchronization engine may be adapted to send acommunication to the storefront to request updated product informationbased on the recommendation. A predictive analytics module may be usedto generate a suggestion to resolve an error, wherein the suggestion maybe communicated to the storefront for approval prior to implementation.A predictive analytics module may be used to generate a suggestion toresolve an error, wherein the suggestion may be automaticallyimplemented. A recommendation may be determined via an analysis oferrors across a group of storefronts for a particular channel. At leastone product information field may be updated based on the analysis oferrors for a storefront not included in the group of storefronts. Thesynchronization engine may be adapted to store received product data asa synchronization data model. The synchronization data model may includefields for requirements of each channel supported by the synchronizationengine. The synchronization data model may be updated in real time. Thesynchronization data model may be updated based on automaticidentification of changes in requirements across channels.

In embodiments, a system may include a synchronization engine that isadapted to perform an analysis of error data, wherein the error data mayinclude identified errors from a prior synchronization, of productinformation to at least one channel and corresponding ways theidentified errors are resolved and determine a recommendation forpreventing a future error synchronizing product data for a storefrontwith a particular channel based on the analysis.

In embodiments, the synchronization engine may be adapted to send acommunication including the recommendation to the storefront. Thecommunication may comprise a request for updated product informationbased on the recommendation. A predictive analytics module may be usedto determine the recommendation and the recommendation may becommunicated to the storefront for approval prior to implementation. Apredictive analytics module may be used to determine the recommendationand the recommendation may be automatically implemented. Therecommendation may be based on error data across a group of storefrontsfor a particular channel. At least one product information field may beautomatically updated for a storefront not included in the group ofstorefronts based on the analysis of error data. The synchronizationengine may use a synchronization data model for translating the productinformation. The synchronization data model may include product datafields required for each channel supported by the synchronizationengine. The synchronization data model may be updated in real time.

In embodiments, a method may include estimating, by a synchronizationengine using error data, future synchronization errors of productinformation to one or more channels. Each channel may have respectiveproduct data fields for that channel and the error data may relate to aprior synchronization of product information from one or morestorefronts to the one or more channels and may include identifiederrors from the prior synchronization and corresponding corrections forresolving at least a subset of the identified errors. Thesynchronization engine may formulate a request to a commerce managementengine associated with the one or more storefronts, wherein the requestrequests product information for one or more products of the one or morestorefronts for a future product synchronization with the one or morechannels and may include a request parameter that may be based on theestimated future synchronization errors.

In embodiments, the synchronization engine may send the request to thecommerce management engine. The request parameter may be a timingparameter that may be based on a predicted time of resolution of atleast some of the estimated future synchronization errors. The requestparameter may be a timing parameter that may include a specified timeperiod for reporting product information changes for the one or moreproducts of the one or more storefronts which occur in the specifiedtime period. The request parameter may be a timing parameter that mayinclude one or more specified times for reporting product informationchanges relative to a prior reporting time for the one or more productsof the one or more storefronts. The request parameter may includespecified products or product fields of the one or more storefronts. Theestimating step may comprise determining if the one or more channelshave new product data fields required for synchronization. The methodmay further include generating a suggestion to provide relevant productdata for a new required product data field, wherein the suggestion maybe automatically implemented. The estimating step may comprise analyzingerror data across a group of storefronts or a group of products for aparticular channel. The estimating step may comprise analyzing errordata on a per channel basis to determine a number of estimated futureerrors per channel, and the future product synchronization may bedelayed for a specific channel if the number of future errors for thechannel is greater than a respective predetermined threshold. The methodmay include analyzing one or more additional factors to determine therequest parameter, wherein the one or more additional factors include acriticality of the errors, a current load on a computing resource of thecommerce management engine, and a predicted additional load on thecommerce management engine based on a request for a specified amount ofproduct information.

In embodiments, the error data may be acquired by receiving, by thesynchronization engine, for each storefront of a plurality ofstorefronts, product information for products and selected channels forthe products, translating, by the synchronization engine for eachstorefront, relevant product information to a translated product formatfor each respective selected channel; and determining, by thesynchronization engine, identified errors in the translated productformats and corresponding ways the identified errors are resolved.

In embodiments, a method may include estimating, by a synchronizationengine using error data, future synchronization errors of productinformation to one or more channels. Each channel may have respectiveproduct data fields for that channel, and the error data may relate to aprior synchronization of product information from one or morestorefronts to the one or more channels and may include identifiederrors from the prior synchronization and corresponding corrections forresolving at least a subset of the identified errors. Thesynchronization engine may determine a load on a computing resource of acommerce management engine associated with the one or more storefronts,wherein the determined load encompasses a current load and/or apredicted future load on the computing resource of the commercemanagement engine. The synchronization engine may formulate a request tothe commerce management engine for product information for one or moreproducts of the one or more storefronts for a future synchronizationwith the one or more channels, wherein the request may include a requestparameter that may be based on the estimated future synchronizationerrors and the determined load.

In embodiments, the computing resource may include at least one of anetwork resource, a processing resource, a database resource, a storageresource, and a memory resource. The determined load may comprise acomposite load value. A request may be delayed if the composite loadvalue may be above a predetermined level. The predetermined level mayvary based on a number of future synchronization errors. The determiningand formulating steps may be performed in an iterative manner. An amountof product information requested by the request may be decreased if thecomposite load value is above a predetermined level. A predicted futureload on the computing resource of the commerce management engine may bedue to a request for a specified amount of product information and/or arequest for a specified computation.

In embodiments, a method may include estimating, by a synchronizationengine using error data, future synchronization errors of productinformation to a plurality of channels, wherein each channel hasrespective product data fields for that channel. The error data mayrelate to a prior synchronization of product information from one ormore storefronts to the plurality of channels and may include identifiederrors from the prior synchronization and corresponding corrections forresolving at least a subset of the identified errors. A determinationmay be made whether each channel of the plurality of channels isaffected by the future synchronization errors to a predetermined extent.A future synchronization of product information to the plurality ofchannels may be delayed if a number of channels affected to thepredetermined extent is above a predetermined threshold.

In embodiments, the future synchronization errors may be categorizedbased on a type of error. The future synchronization errors may bedetermined on a per channel basis and a future synchronization ofproduct information to a specific channel may be delayed if the specificchannel is affected to the predetermined extent. The predeterminedextent may relate to a number or a type of future synchronizationerrors. The future synchronization may be delayed for all the channelsof the plurality of channels. Product information may be synchronized tothe plurality of channels once the future synchronization errors areresolved. Product information may be synchronized to a channel of theplurality of channels if the future synchronization errors are resolvedsuch that the channel is no longer affected to the predetermined extent.Product information may be synchronized to the plurality of channels ifthe future synchronization errors are resolved such that the number ofchannels affected is below the predetermined threshold.

In embodiments, a system may include a synchronization engine, whereinthe synchronization engine is adapted to estimate, using error data,future synchronization errors of product information to one or morechannels, wherein each channel has respective product data fields forthat channel. The error data may relate to a prior synchronization ofproduct information from one or more storefronts to the one or morechannels and may include identified errors from the priorsynchronization and corresponding corrections for resolving at least asubset of the identified errors. The synchronization engine may beadapted to formulate a request to a commerce management engineassociated with the one or more storefronts, wherein the requestrequests product information for one or more products of the one or morestorefronts for a future product synchronization with the one or morechannels and may include a request parameter that is based on theestimated future synchronization errors.

In embodiments, the synchronization engine is adapted to send therequest to the commerce management engine. The request parameter may bea timing parameter that may be based on a predicted time of resolutionof at least some of the estimated future synchronization errors. Therequest parameter may be a timing parameter that may include a specifiedtime period for reporting product information changes for the one ormore products of the one or more storefronts which occur in thespecified time period. The request parameter may be a timing parameterthat may include one or more specified times for reporting productinformation changes relative to a prior reporting time for the one ormore products of the one or more storefronts. The request parameter mayinclude specified products or product fields of the one or morestorefronts. The estimating step may comprise determining if the one ormore channels have new product data fields required for synchronization.A suggestion to provide relevant product data for a new required productdata field may be generated, wherein the suggestion may be automaticallyimplemented. The estimating step may comprise analyzing error dataacross a group of storefronts or a group of products for a particularchannel. The estimating step may comprise analyzing error data on a perchannel basis, to determine a number of estimated future errors perchannel. A future product synchronization may be delayed for a specificchannel if the number of future errors for the channel is greater than arespective predetermined threshold. The synchronization engine may beadapted to analyze one or more additional factors to determine therequest parameter, wherein the one or more additional factors include acriticality of the errors, a current load on a computing resource of thecommerce management engine, and/or a predicted additional load on thecommerce management engine based on a request for a specified amount ofproduct information. In embodiments, the synchronization engine may beadapted to acquire the error data by receiving, for each storefront of aplurality of storefronts, product information for products and selectedchannels for the products, translating, for each storefront, relevantproduct information to a translated product format for each respectiveselected channel, and determining, by the synchronization engine,identified errors in the translated product formats and correspondingways the identified errors are resolved.

In embodiments, a system includes a synchronization engine that isadapted to estimate, using error data, future synchronization errors ofproduct information to one or more channels. Each channel may haverespective product data fields for that channel. The error data mayrelate to a prior synchronization of product information from one ormore storefronts to the one or more channels and may include identifiederrors from the prior synchronization and corresponding corrections forresolving at least a subset of the identified errors. Thesynchronization engine may determine a load on a computing resource of acommerce management engine associated with the one or more storefronts.The determined load may encompass a current load and/or a predictedfuture load on the computing resource of the commerce management engine.The synchronization engine may formulate a request to the commercemanagement engine for product information for one or more products ofthe one or more storefronts for a future synchronization with the one ormore channels. The request may include a request parameter that may bebased on the estimated future synchronization errors and the determinedload.

In embodiments, the computing resource may include a network resource, aprocessing resource, a database resource, a storage resource, and/or amemory resource. The determined load may comprise a composite loadvalue. A request may be delayed if the composite load value is above apredetermined level. The predetermined level may vary based on a numberof future synchronization errors. The determining and formulating stepsmay be performed by the synchronization engine in an iterative manner.An amount of product information requested by the request may bedecreased if the composite load value is above a predetermined level. Apredicted future load on the computing resource of the commercemanagement engine may be due to a request for a specified amount ofproduct information and/or a request for a specified computation.

In embodiments, a system may include a synchronization engine that isadapted to estimate, using error data, future synchronization errors ofproduct information to a plurality of channels. Each channel may haverespective product data fields for that channel. The error data mayrelate to a prior synchronization of product information from one ormore storefronts to the plurality of channels and may include identifiederrors from the prior synchronization and corresponding corrections forresolving at least a subset of the identified errors. Thesynchronization engine may be adapted to determine whether each channelof the plurality of channels is affected by the future synchronizationerrors to a predetermined extent. A future synchronization of productinformation to the plurality of channels may be delayed if a number ofchannels affected to the predetermined extent is above a predeterminedthreshold.

In embodiments, the future synchronization errors may be categorizedbased on a type of error. The future synchronization errors may bedetermined on a per channel basis and a future synchronization ofproduct information to a specific channel may be delayed if the specificchannel is affected to the predetermined extent. The predeterminedextent may relate to a number or a type of future synchronizationerrors. The future synchronization may be delayed for all the channelsof the plurality of channels. The synchronization engine may be adaptedto synchronize product information to the plurality of channels once thefuture synchronization errors are resolved. The synchronization enginemay be adapted to synchronize product information to a channel of theplurality of channels if the future synchronization errors are resolvedsuch that the channel is no longer affected to the predetermined extent.The synchronization engine may be adapted to synchronize productinformation to the plurality of channels if the future synchronizationerrors are resolved such that the number of channels affected is belowthe predetermined threshold.

BRIEF DESCRIPTION OF THE FIGURES

FIG. 1 depicts an embodiment of an e-commerce platform.

FIG. 2 depicts an embodiment for a home page of an administrator.

FIG. 3 depicts an embodiment of a block diagram of a synchronizationengine.

FIG. 4 depicts an exemplary process for using error data from asynchronization of product data to one or more channels to determine arecommendation for preventing a future synchronization error.

FIG. 5A depicts an exemplary process for using error data from a priorsynchronization of product data to one or more channels to control aparameter of a request for product information from the e-commerceplatform.

FIG. 5B depicts an exemplary process for using error data from a priorsynchronization of product data to one or more channels and adetermination of a load on computing resources of the commercemanagement engine to control a parameter of a request for productinformation from the e-commerce platform.

FIG. 5C depicts an exemplary process for using estimated futuresynchronization errors across channels to determine timing of futuresynchronizations for one or more channels.

FIG. 6 depicts an exemplary user interface for displaying identifiederrors to a merchant.

FIG. 7 depicts an exemplary user interface for displaying consolidatederrors for channels.

FIGS. 8 and 9 depict exemplary user interfaces utilizing asynchronization data model to depict which product data fields arerequired for a particular channel.

DETAILED DESCRIPTION

The present disclosure will now be described in detail by describingvarious illustrative, non-limiting embodiments thereof with reference tothe accompanying drawings and exhibits. The disclosure may, however, beembodied in many different forms and should not be construed as beinglimited to the illustrative embodiments set forth herein. Rather, theembodiments are provided so that this disclosure will be thorough andwill fully convey the concept of the disclosure to those skilled in theart.

With reference to FIG. 1, an embodiment e-commerce platform 100 isdepicted for providing merchant products and services to customers.While the disclosure throughout contemplates using the apparatus,system, and process disclosed to purchase products and services, forsimplicity the description herein will refer to products. All referencesto products throughout this disclosure should also be understood to bereferences to products and/or services, including physical products,digital content, tickets, subscriptions, services to be provided, andthe like.

While the disclosure throughout contemplates that a ‘merchant’ and a‘customer’ may be more than individuals, for simplicity the descriptionherein may generally refer to merchants and customers as such. Allreferences to merchants and customers throughout this disclosure shouldalso be understood to be references to groups of individuals, companies,corporations, computing entities, and the like, and may representfor-profit or not-for-profit exchange of products. Further, while thedisclosure throughout refers to ‘merchants’ and ‘customers’, anddescribes their roles as such, the e-commerce platform 100 should beunderstood to more generally support users in an e-commerce environment,and all references to merchants and customers throughout this disclosureshould also be understood to be references to users, such as where auser is a merchant-user (e.g., a seller, retailer, wholesaler, orprovider of products), a customer-user (e.g., a buyer, purchase agent,or user of products), a prospective user (e.g., a user browsing and notyet committed to a purchase, a user evaluating the e-commerce platform100 for potential use in marketing and selling products, and the like),a service provider user (e.g., a shipping provider 112, a financialprovider, and the like), a company or corporate user (e.g., a companyrepresentative for purchase, sales, or use of products; an enterpriseuser; a customer relations or customer management agent, and the like),an information technology user, a computing entity user (e.g., acomputing bot for purchase, sales, or use of products), and the like.

The e-commerce platform 100 may provide a centralized system forproviding merchants with online resources and facilities for managingtheir business. The facilities described herein may be deployed in partor in whole through a machine that executes computer software, modules,program codes, and/or instructions on one or more processors which maybe part of or external to the platform 100. Merchants may utilize thee-commerce platform 100 for managing commerce with customers, such as byimplementing an e-commerce experience with customers through an onlinestore 138, through channels 110A-B, through POS devices 152 in physicallocations (e.g., a physical storefront or other location such as througha kiosk, terminal, reader, printer, 3D printer, and the like), bymanaging their business through the e-commerce platform 100, and byinteracting with customers through a communications facility 129 of thee-commerce platform 100, or any combination thereof. A merchant mayutilize the e-commerce platform 100 as a sole commerce presence withcustomers, or in conjunction with other merchant commerce facilities,such as through a physical store (e.g., ‘brick-and-mortar’ retailstores), a merchant off-platform website 104 (e.g., a commerce Internetwebsite or other internet or web property or asset supported by or onbehalf of the merchant separately from the e-commerce platform), and thelike. However, even these ‘other’ merchant commerce facilities may beincorporated into the e-commerce platform, such as where POS devices 152in a physical store of a merchant are linked into the e-commerceplatform 100, where a merchant off-platform website 104 is tied into thee-commerce platform 100, such as through ‘buy buttons’ that link contentfrom the merchant off platform website 104 to the online store 138, andthe like.

The online store 138 may represent a multitenant facility comprising aplurality of virtual storefronts. In embodiments, merchants may manageone or more storefronts in the online store 138, such as through amerchant device 102 (e.g., computer, laptop computer, mobile computingdevice, and the like), and offer products to customers through a numberof different channels 110A-B (e.g., an online store 138; a physicalstorefront through a POS device 152; electronic marketplace, through anelectronic buy button integrated into a website or social media channelsuch as on a social network, social media page, social media messagingsystem; and the like). A merchant may sell across channels 110A-B andthen manage their sales through the e-commerce platform 100, wherechannels 110A may be provided internal to the e-commerce platform 100 orfrom outside the e-commerce channel 110B. A merchant may sell in theirphysical retail store, at pop ups, through wholesale, over the phone,and the like, and then manage their sales through the e-commerceplatform 100. A merchant may employ all or any combination of these,such as maintaining a business through a physical storefront utilizingPOS devices 152, maintaining a virtual storefront through the onlinestore 138, and utilizing a communication facility 129 to leveragecustomer interactions and analytics 132 to improve the probability ofsales. Throughout this disclosure the terms online store 138 andstorefront may be used synonymously to refer to a merchant's onlinee-commerce offering presence through the e-commerce platform 100, wherean online store 138 may refer to the multitenant collection ofstorefronts supported by the e-commerce platform 100 (e.g., for aplurality of merchants) or to an individual merchant's storefront (e.g.,a merchant's online store). Throughout this disclosure the terms onlinestore 138 and storefront may be used in connection with an onlinee-commerce presence, an offline commerce presence (such as a physicalstore), an online channel, an offline channel, a channel 110A internalto the platform 100, a channel 110B external to the platform 100, or thelike, or any combination of the foregoing.

In embodiments, a customer may interact through a customer device 150(e.g., computer, laptop computer, mobile computing device, and thelike), a POS device 152 (e.g., retail device, a kiosk, an automatedcheckout system, and the like), or any other commerce interface deviceknown in the art. The e-commerce platform 100 may enable merchants toreach customers through the online store 138, through POS devices 152 inphysical locations (e.g., a merchant's storefront or elsewhere), topromote commerce with customers through dialog via electroniccommunication facility 129, and the like, providing a system forreaching customers and facilitating merchant services for the real orvirtual pathways available for reaching and interacting with customers.

In embodiments, and as described further herein, the e-commerce platform100 may be implemented through a processing facility including aprocessor and a memory, the processing facility storing a set ofinstructions that, when executed, cause the e-commerce platform 100 toperform the e-commerce and support functions as described herein. Theprocessing facility may be part of a server, client, networkinfrastructure, mobile computing platform, cloud computing platform,stationary computing platform, or other computing platform, and provideelectronic connectivity and communications between and amongst theelectronic components of the e-commerce platform 100, merchant devices102, payment gateways 106, application developers, channels 110A-B,shipping providers 112, customer devices 150, point of sale devices 152,and the like. The e-commerce platform 100 may be implemented as a cloudcomputing service, a software as a service (SaaS), infrastructure as aservice (IaaS), platform as a service (PaaS), desktop as a Service(DaaS), managed software as a service (MSaaS), mobile backend as aservice (MBaaS), information technology management as a service(ITMaaS), and the like, such as in a software and delivery model inwhich software is licensed on a subscription basis and centrally hosted(e.g., accessed by users using a client (for example, a thin client) viaa web browser or other application, accessed through by POS devices, andthe like). In embodiments, elements of the e-commerce platform 100 maybe implemented to operate on various platforms and operating systems,such as iOS, Android, on the web, and the like (e.g., the administrator114 being implemented in multiple instances for a given online store foriOS, Android, and for the web, each with similar functionality).

In embodiments, the online store 138 may be served to a customer device150 through a webpage provided by a server of the e-commerce platform100. The server may receive a request for the webpage from a browser orother application installed on the customer device 150, where thebrowser (or other application) connects to the server through an IPAddress, the IP address obtained by translating a domain name. Inreturn, the server sends back the requested webpage. Webpages may bewritten in or include Hypertext Markup Language (HTML), templatelanguage, JavaScript, and the like, or any combination thereof. Forinstance, HTML is a computer language that describes static informationfor the webpage, such as the layout, format, and content of the webpage.Website designers and developers may use the template language to buildwebpages that combine static content, which is the same on multiplepages, and dynamic content, which changes from one page to the next. Atemplate language may make it possible to re-use the static elementsthat define the layout of a webpage, while dynamically populating thepage with data from an online store. The static elements may be writtenin HTML, and the dynamic elements written in the template language. Thetemplate language elements in a file may act as placeholders, such thatthe code in the file is compiled and sent to the customer device 150 andthen the template language is replaced by data from the online store138, such as when a theme is installed. The template and themes mayconsider tags, objects, and filters. The client device web browser (orother application) then renders the page accordingly.

In embodiments, online stores 138 may be served by the e-commerceplatform 100 to customers, where customers can browse and purchase thevarious products available (e.g., add them to a cart, purchaseimmediately through a buy-button, and the like). Online stores 138 maybe served to customers in a transparent fashion without customersnecessarily being aware that it is being provided through the e-commerceplatform 100 (rather than directly from the merchant). Merchants may usea merchant configurable domain name, a customizable HTML theme, and thelike, to customize their online store 138. Merchants may customize thelook and feel of their website through a theme system, such as wheremerchants can select and change the look and feel of their online store138 by changing their theme while having the same underlying product andbusiness data shown within the online store's product hierarchy. Themesmay be further customized through a theme editor, a design interfacethat enables users to customize their website's design with flexibility.Themes may also be customized using theme-specific settings that changeaspects, such as specific colors, fonts, and pre-built layout schemes.The online store may implement a content management system for websitecontent. Merchants may author blog posts or static pages and publishthem to their online store 138, such as through blogs, articles, and thelike, as well as configure navigation menus. Merchants may upload images(e.g., for products), video, content, data, and the like to thee-commerce platform 100, such as for storage by the system (e.g. as data134). In embodiments, the e-commerce platform 100 may provide functionsfor resizing images, associating an image with a product, adding andassociating text with an image, adding an image for a new productvariant, protecting images, and the like.

As described herein, the e-commerce platform 100 may provide merchantswith transactional facilities for products through a number of differentchannels 110A-B, including the online store 138, over the telephone, aswell as through physical POS devices 152 as described herein. Thee-commerce platform 100 may include business support services 116, anadministrator 114, and the like associated with running an on-linebusiness, such as providing a domain service 118 associated with theironline store, payment services 120 for facilitating transactions with acustomer, shipping services 122 for providing customer shipping optionsfor purchased products, risk and insurance services 124 associated withproduct protection and liability, merchant billing, and the like.Services 116 may be provided via the e-commerce platform 100 or inassociation with external facilities, such as through a payment gateway106 for payment processing, shipping providers 112 for expediting theshipment of products, and the like.

In embodiments, the e-commerce platform 100 may provide for integratedshipping services 122 (e.g., through an e-commerce platform shippingfacility or through a third-party shipping carrier), such as providingmerchants with real-time updates, tracking, automatic rate calculation,bulk order preparation, label printing, and the like.

FIG. 2 depicts a non-limiting embodiment for a home page of anadministrator 114, which may show information about daily tasks, astore's recent activity, and the next steps a merchant can take to buildtheir business. In embodiments, a merchant may log in to administrator114 via a merchant device 102 such as from a desktop computer or mobiledevice, and manage aspects of their online store 138, such as viewingthe online store's 138 recent activity, updating the online store's 138catalog, managing orders, recent visits activity, total orders activity,and the like. In embodiments, the merchant may be able to access thedifferent sections of administrator 114 by using the sidebar, such asshown on FIG. 2. Sections of the administrator 114 may include variousinterfaces for accessing and managing core aspects of a merchant'sbusiness, including orders, products, customers, available reports anddiscounts. The administrator 114 may also include interfaces formanaging sales channels for a store including the online store, mobileapplication(s) made available to customers for accessing the store(Mobile App), POS devices, and/or a buy button. The administrator 114may also include interfaces for managing applications (Apps) installedon the merchant's account; settings applied to a merchant's online store138 and account. A merchant may use a search bar to find products,pages, or other information. Depending on the device 102 or softwareapplication the merchant is using, they may be enabled for differentfunctionality through the administrator 114. For instance, if a merchantlogs in to the administrator 114 from a browser, they may be able tomanage all aspects of their online store 138. If the merchant logs infrom their mobile device (e.g. via a mobile application), they may beable to view all or a subset of the aspects of their online store 138,such as viewing the online store's 138 recent activity, updating theonline store's 138 catalog, managing orders, and the like.

More detailed information about commerce and visitors to a merchant'sonline store 138 may be viewed through acquisition reports or metrics,such as displaying a sales summary for the merchant's overall business,specific sales and engagement data for active sales channels, and thelike. Reports may include, acquisition reports, behavior reports,customer reports, finance reports, marketing reports, sales reports,custom reports, and the like. The merchant may be able to view salesdata for different channels 110A-B from different periods of time (e.g.,days, weeks, months, and the like), such as by using drop-down menus. Anoverview dashboard may be provided for a merchant that wants a moredetailed view of the store's sales and engagement data. An activity feedin the home metrics section may be provided to illustrate an overview ofthe activity on the merchant's account. For example, by clicking on a‘view all recent activity’ dashboard button, the merchant may be able tosee a longer feed of recent activity on their account. A home page mayshow notifications about the merchant's online store 138, such as basedon account status, growth, recent customer activity, and the like.Notifications may be provided to assist a merchant with navigatingthrough a process, such as capturing a payment, marking an order asfulfilled, archiving an order that is complete, and the like.

The e-commerce platform 100 may provide for a communications facility129 and associated merchant interface for providing electroniccommunications and marketing, such as utilizing an electronic messagingaggregation facility for collecting and analyzing communicationinteractions between merchants, customers, merchant devices 102,customer devices 150, POS devices 152, and the like, to aggregate andanalyze the communications, such as for increasing the potential forproviding a sale of a product, and the like. For instance, a customermay have a question related to a product, which may produce a dialogbetween the customer and the merchant (or automated processor-basedagent representing the merchant), where the communications facility 129analyzes the interaction and provides analysis to the merchant on how toimprove the probability for a sale.

The e-commerce platform 100 may provide a financial facility 120 forsecure financial transactions with customers, such as through a securecard server environment. The e-commerce platform 100 may store creditcard information, such as in payment card industry data (PCI)environments (e.g., a card server), to reconcile financials, billmerchants, perform automated clearing house (ACH) transfers between ane-commerce platform 100 financial institution account and a merchant'sback account (e.g., when using capital), and the like. These systems mayhave Sarbanes-Oxley Act (SOX) compliance and a high level of diligencerequired in their development and operation. The financial facility 120may also provide merchants with financial support, such as through thelending of capital (e.g., lending funds, cash advances, and the like)and provision of insurance. In addition, the e-commerce platform 100 mayprovide for a set of marketing and partner services and control therelationship between the e-commerce platform 100 and partners. They alsomay connect and onboard new merchants with the e-commerce platform 100.These services may enable merchant growth by making it easier formerchants to work across the e-commerce platform 100. Through theseservices, merchants may be provided help facilities via the e-commerceplatform 100.

In embodiments, online store 138 may support a great number ofindependently administered storefronts and process a large volume oftransactional data on a daily basis for a variety of products.Transactional data may include customer contact information, billinginformation, shipping information, information on products purchased,information on services rendered, and any other information associatedwith business through the e-commerce platform 100. In embodiments, thee-commerce platform 100 may store this data in a data facility 134. Thetransactional data may be processed to produce analytics 132, which inturn may be provided to merchants or third-party commerce entities, suchas providing consumer trends, marketing and sales insights,recommendations for improving sales, evaluation of customer behaviors,marketing and sales modeling, trends in fraud, and the like, related toonline commerce, and provided through dashboard interfaces, throughreports, and the like. The e-commerce platform 100 may store informationabout business and merchant transactions, and the data facility 134 mayhave many ways of enhancing, contributing, refining, and extractingdata, where over time the collected data may enable improvements toaspects of the e-commerce platform 100.

Referring again to FIG. 1, in embodiments the e-commerce platform 100may be configured with a commerce management engine 136 for contentmanagement, task automation and data management to enable support andservices to the plurality of online stores 138 (e.g., related toproducts, inventory, customers, orders, collaboration, suppliers,reports, financials, risk and fraud, and the like), but be extensiblethrough applications 142A-B that enable greater flexibility and customprocesses required for accommodating an ever-growing variety of merchantonline stores, POS devices, products, and services, where applications142A may be provided internal to the e-commerce platform 100 orapplications 142B from outside the e-commerce platform 100. Inembodiments, an application 142A may be provided by the same partyproviding the platform 100 or by a different party. In embodiments, anapplication 142B may be provided by the same party providing theplatform 100 or by a different party. The commerce management engine 136may be configured for flexibility and scalability through portioning(e.g., sharding) of functions and data, such as by customer identifier,order identifier, online store identifier, and the like. The commercemanagement engine 136 may accommodate store-specific business logic andin some embodiments, may incorporate the administrator 114 and/or theonline store 138.

The commerce management engine 136 includes base or “core” functions ofthe e-commerce platform 100, and as such, as described herein, not allfunctions supporting online stores 138 may be appropriate for inclusion.For instance, functions for inclusion into the commerce managementengine 136 may need to exceed a core functionality threshold throughwhich it may be determined that the function is core to a commerceexperience (e.g., common to a majority of online store activity, such asacross channels, administrator interfaces, merchant locations,industries, product types, and the like), is re-usable across onlinestores 138 (e.g., functions that can be re-used/modified across corefunctions), limited to the context of a single online store 138 at atime (e.g., implementing an online store ‘isolation principle’, wherecode should not be able to interact with multiple online stores 138 at atime, ensuring that online stores 138 cannot access each other's data),provide a transactional workload, and the like. Maintaining control ofwhat functions are implemented may enable the commerce management engine136 to remain responsive, as many required features are either serveddirectly by the commerce management engine 136 or enabled through aninterface 140A-B, such as by its extension through an applicationprogramming interface (API) connection to applications 142A-B andchannels 110A-B, where interfaces 140A may be provided to applications142A and/or channels 110A inside the e-commerce platform 100 or throughinterfaces 140B provided to applications 142B and/or channels 110Boutside the e-commerce platform 100. Generally, the platform 100 mayinclude interfaces 140A-B (which may be extensions, connectors, APIs,and the like) which facilitate connections to and communications withother platforms, systems, software, data sources, code and the like.Such interfaces 140A-B may be an interface 140A of the commercemanagement engine 136 or an interface 140B of the platform 100 moregenerally. If care is not given to restricting functionality in thecommerce management engine 136, responsiveness could be compromised,such as through infrastructure degradation through slow databases ornon-critical backend failures, through catastrophic infrastructurefailure such as with a data center going offline, through new code beingdeployed that takes longer to execute than expected, and the like. Toprevent or mitigate these situations, the commerce management engine 136may be configured to maintain responsiveness, such as throughconfiguration that utilizes timeouts, queues, back-pressure to preventdegradation, and the like.

Although isolating online store data is important to maintaining dataprivacy between online stores 138 and merchants, there may be reasonsfor collecting and using cross-store data, such as for example, with anorder risk assessment system or a platform payment facility, both ofwhich require information from multiple online stores 138 to performwell. In embodiments, rather than violating the isolation principle, itmay be preferred to move these components out of the commerce managementengine 136 and into their own infrastructure within the e-commerceplatform 100.

In embodiments, the e-commerce platform 100 may provide for a platformpayment facility 120, which is another example of a component thatutilizes data from the commerce management engine 136 but may be locatedoutside so as to not violate the isolation principle. The platformpayment facility 120 may allow customers interacting with online stores138 to have their payment information stored safely by the commercemanagement engine 136 such that they only have to enter it once. When acustomer visits a different online store 138, even if they've never beenthere before, the platform payment facility 120 may recall theirinformation to enable a more rapid and correct check out. This mayprovide a cross-platform network effect, where the e-commerce platform100 becomes more useful to its merchants as more merchants join, such asbecause there are more customers who checkout more often because of theease of use with respect to customer purchases. To maximize the effectof this network, payment information for a given customer may beretrievable from an online store's checkout, allowing information to bemade available globally across online stores 138. It would be difficultand error prone for each online store 138 to be able to connect to anyother online store 138 to retrieve the payment information stored there.As a result, the platform payment facility may be implemented externalto the commerce management engine 136.

For those functions that are not included within the commerce managementengine 136, applications 142A-B provide a way to add features to thee-commerce platform 100. Applications 142A-B may be able to access andmodify data on a merchant's online store 138, perform tasks through theadministrator 114, create new flows for a merchant through a userinterface (e.g., that is surfaced through extensions/API), and the like.Merchants may be enabled to discover and install applications 142A-Bthrough application search, recommendations, and support 128. Inembodiments, core products, core extension points, applications, and theadministrator 114 may be developed to work together. For instance,application extension points may be built inside the administrator 114so that core features may be extended by way of applications, which maydeliver functionality to a merchant through the extension.

In embodiments, applications 142A-B may deliver functionality to amerchant through the interface 140A-B, such as where an application142A-B is able to surface transaction data to a merchant (e.g., App:“Engine, surface my app data in mobile and web admin using the embeddedapp SDK”), and/or where the commerce management engine 136 is able toask the application to perform work on demand (Engine: “App, give me alocal tax calculation for this checkout”).

Applications 142A-B may support online stores 138 and channels 110A-B,provide for merchant support, integrate with other services, and thelike. Where the commerce management engine 136 may provide thefoundation of services to the online store 138, the applications 142A-Bmay provide a way for merchants to satisfy specific and sometimes uniqueneeds. Different merchants will have different needs, and so may benefitfrom different applications 142A-B. Applications 142A-B may be betterdiscovered through the e-commerce platform 100 through development of anapplication taxonomy (categories) that enable applications to be taggedaccording to a type of function it performs for a merchant; throughapplication data services that support searching, ranking, andrecommendation models; through application discovery interfaces such asan application store, home information cards, an application settingspage; and the like.

Applications 142A-B may be connected to the commerce management engine136 through an interface 140A-B, such as utilizing APIs to expose thefunctionality and data available through and within the commercemanagement engine 136 to the functionality of applications (e.g.,through REST, GraphQL, and the like). For instance, the e-commerceplatform 100 may provide API interfaces 140A-B to merchant andpartner-facing products and services, such as including applicationextensions, process flow services, developer-facing resources, and thelike. With customers more frequently using mobile devices for shopping,applications 142A-B related to mobile use may benefit from moreextensive use of APIs to support the related growing commerce traffic.The flexibility offered through use of applications and APIs (e.g., asoffered for application development) enable the e-commerce platform 100to better accommodate new and unique needs of merchants (and internaldevelopers through internal APIs) without requiring constant change tothe commerce management engine 136, thus providing merchants what theyneed when they need it. For instance, shipping services 122 may beintegrated with the commerce management engine 136 through a shipping orcarrier service API, thus enabling the e-commerce platform 100 toprovide shipping service functionality without directly impacting coderunning in the commerce management engine 136.

Many merchant problems may be solved by letting partners improve andextend merchant workflows through application development, such asproblems associated with back-office operations (merchant-facingapplications 142A-B) and in the online store 138 (customer-facingapplications 142A-B). As a part of doing business, many merchants willuse mobile and web related applications on a daily basis for back-officetasks (e.g., merchandising, inventory, discounts, fulfillment, and thelike) and online store tasks (e.g., applications related to their onlineshop, for flash-sales, new product offerings, and the like), whereapplications 142A-B, through extension/API 140A-B, help make productseasy to view and purchase in a fast growing marketplace. In embodiments,partners, application developers, internal applications facilities, andthe like, may be provided with a software development kit (SDK), such asthrough creating a frame within the administrator 114 that sandboxes anapplication interface. In embodiments, the administrator 114 may nothave control over nor be aware of what happens within the frame. The SDKmay be used in conjunction with a user interface kit to produceinterfaces that mimic the look and feel of the e-commerce platform 100,such as acting as an extension of the commerce management engine 136.

Applications 142A-B that utilize APIs may pull data on demand, but oftenthey also need to have data pushed when updates occur. Update events maybe implemented in a subscription model, such as for example, customercreation, product changes, or order cancelation. Update events mayprovide merchants with needed updates with respect to a changed state ofthe commerce management engine 136, such as for synchronizing a localdatabase, notifying an external integration partner, and the like.Update events may enable this functionality without having to poll thecommerce management engine 136 all the time to check for updates, suchas through an update event subscription. In embodiments, when a changerelated to an update event subscription occurs, the commerce managementengine 136 may post a request, such as to a predefined callback URL. Thebody of this request may contain a new state of the object and adescription of the action or event. Update event subscriptions may becreated manually, in the administrator facility 114, or automatically(e.g., via the API 140A-B). In embodiments, update events may be queuedand processed asynchronously from a state change that triggered them,which may produce an update event notification that is not distributedin real-time.

In embodiments, the e-commerce platform 100 may provide applicationsearch, recommendation and support 128. Application search,recommendation and support 128 may include developer products and toolsto aid in the development of applications, an application dashboard(e.g., to provide developers with a development interface, toadministrators for management of applications, to merchants forcustomization of applications, and the like), facilities for installingand providing permissions with respect to providing access to anapplication 142A-B (e.g., for public access, such as where criteria mustbe met before being installed, or for private use by a merchant),application searching to make it easy for a merchant to search forapplications 142A-B that satisfy a need for their online store 138,application recommendations to provide merchants with suggestions on howthey can improve the user experience through their online store 138, adescription of core application capabilities within the commercemanagement engine 136, and the like. These support facilities may beutilized by application development performed by any entity, includingthe merchant developing their own application 142A-B, a third-partydeveloper developing an application 142A-B (e.g., contracted by amerchant, developed on their own to offer to the public, contracted foruse in association with the e-commerce platform 100, and the like), oran application 142A or 142B being developed by internal personalresources associated with the e-commerce platform 100. In embodiments,applications 142A-B may be assigned an application identifier (ID), suchas for linking to an application (e.g., through an API), searching foran application, making application recommendations, and the like.

The commerce management engine 136 may include base functions of thee-commerce platform 100 and expose these functions through APIs 140A-Bto applications 142A-B. The APIs 140A-B may enable different types ofapplications built through application development. Applications 142A-Bmay be capable of satisfying a great variety of needs for merchants butmay be grouped roughly into three categories: customer-facingapplications, merchant-facing applications, integration applications,and the like. Customer-facing applications 142A-B may include onlinestore 138 or channels 110A-B that are places where merchants can listproducts and have them purchased (e.g., the online store, applicationsfor flash sales (e.g., merchant products or from opportunistic salesopportunities from third-party sources), a mobile store application, asocial media channel, an application for providing wholesale purchasing,and the like). Merchant-facing applications 142A-B may includeapplications that allow the merchant to administer their online store138 (e.g., through applications related to the web or website or tomobile devices), run their business (e.g., through applications relatedto POS devices), to grow their business (e.g., through applicationsrelated to shipping (e.g., drop shipping), use of automated agents, useof process flow development and improvements), and the like. Integrationapplications may include applications that provide useful integrationsthat participate in the running of a business, such as shippingproviders 112 and payment gateways.

In embodiments, an application developer may use an application proxy tofetch data from an outside location and display it on the page of anonline store 138. Content on these proxy pages may be dynamic, capableof being updated, and the like. Application proxies may be useful fordisplaying image galleries, statistics, custom forms, and other kinds ofdynamic content. The core-application structure of the e-commerceplatform 100 may allow for an increasing number of merchant experiencesto be built in applications 142A-B so that the commerce managementengine 136 can remain focused on the more commonly utilized businesslogic of commerce.

The e-commerce platform 100 provides an online shopping experiencethrough a curated system architecture that enables merchants to connectwith customers in a flexible and transparent manner. A typical customerexperience may be better understood through an embodiment examplepurchase workflow, where the customer browses the merchant's products ona channel 110A-B, adds what they intend to buy to their cart, proceedsto checkout, and pays for the content of their cart resulting in thecreation of an order for the merchant. The merchant may then review andfulfill (or cancel) the order. The product is then delivered to thecustomer. If the customer is not satisfied, they might return theproducts to the merchant.

In an example embodiment, a customer may browse a merchant's products ona channel 110A-B. A channel 110A-B is a place where customers can viewand buy products. In embodiments, channels 110A-B may be modeled asapplications 142A-B (a possible exception being the online store 138,which is integrated within the commence management engine 136). Amerchandising component may allow merchants to describe what they wantto sell and where they sell it. The association between a product and achannel may be modeled as a product publication and accessed by channelapplications, such as via a product listing API. A product may have manyoptions, like size and color, and many variants that expand theavailable options into specific combinations of all the options, likethe variant that is extra-small and green, or the variant that is sizelarge and blue. Products may have at least one variant (e.g., a “defaultvariant” is created for a product without any options). To facilitatebrowsing and management, products may be grouped into collections,provided product identifiers (e.g., stock keeping unit (SKU)) and thelike. Collections of products may be built by either manuallycategorizing products into one (e.g., a custom collection), by buildingrulesets for automatic classification (e.g., a smart collection), andthe like. Products may be viewed as 2D images, 3D images, rotating viewimages, through a virtual or augmented reality interface, and the like.

In embodiments, the customer may add what they intend to buy to theircart (in an alternate embodiment, a product may be purchased directly,such as through a buy button as described herein). Customers may addproduct variants to their shopping cart. The shopping cart model may bechannel specific. The online store 138 cart may be composed of multiplecart line items, where each cart line item tracks the quantity for aproduct variant. Merchants may use cart scripts to offer specialpromotions to customers based on the content of their cart. Since addinga product to a cart does not imply any commitment from the customer orthe merchant, and the expected lifespan of a cart may be in the order ofminutes (not days), carts may be persisted to an ephemeral data store.

The customer then proceeds to checkout. A checkout component mayimplement a web checkout as a customer-facing order creation process. Acheckout API may be provided as a computer-facing order creation processused by some channel applications to create orders on behalf ofcustomers (e.g., for point of sale). Checkouts may be created from acart and record a customer's information such as email address, billing,and shipping details. On checkout, the merchant commits to pricing. Ifthe customer inputs their contact information but does not proceed topayment, the e-commerce platform 100 may provide an opportunity tore-engage the customer (e.g., in an abandoned checkout feature). Forthose reasons, checkouts can have much longer lifespans than carts(hours or even days) and are therefore persisted. Checkouts maycalculate taxes and shipping costs based on the customer's shippingaddress. Checkout may delegate the calculation of taxes to a taxcomponent and the calculation of shipping costs to a delivery component.A pricing component may enable merchants to create discount codes (e.g.,‘secret’ strings that when entered on the checkout apply new prices tothe items in the checkout). Discounts may be used by merchants toattract customers and assess the performance of marketing campaigns.Discounts and other custom price systems may be implemented on top ofthe same platform piece, such as through price rules (e.g., a set ofprerequisites that when met imply a set of entitlements). For instance,prerequisites may be items such as “the order subtotal is greater than$100” or “the shipping cost is under $10”, and entitlements may be itemssuch as “a 20% discount on the whole order” or “$10 off products X, Y,and Z”.

Customers then pay for the content of their cart resulting in thecreation of an order for the merchant. Channels 110A-B may use thecommerce management engine 136 to move money, currency or a store ofvalue (such as dollars or a cryptocurrency) to and from customers andmerchants. Communication with the various payment providers (e.g.,online payment systems, mobile payment systems, digital wallet, creditcard gateways, and the like) may be implemented within a paymentprocessing component. The actual interactions with the payment gateways106 may be provided through a card server environment. In embodiments,the payment gateway 106 may accept international payment, such asintegrating with leading international credit card processors. The cardserver environment may include a card server application, card sink,hosted fields, and the like. This environment may act as the securegatekeeper of the sensitive credit card information. In embodiments,most of the process may be orchestrated by a payment processing job. Thecommerce management engine 136 may support many other payment methods,such as through an offsite payment gateway 106 (e.g., where the customeris redirected to another website), manually (e.g., cash), online paymentmethods (e.g., online payment systems, mobile payment systems, digitalwallet, credit card gateways, and the like), gift cards, and the like.At the end of the checkout process, an order is created. An order is acontract of sale between the merchant and the customer where themerchant agrees to provide the goods and services listed on the orders(e.g., order line items, shipping line items, and the like) and thecustomer agrees to provide payment (including taxes). This process maybe modeled in a sales component. Channels 110A-B that do not rely oncommerce management engine 136 checkouts may use an order API to createorders. Once an order is created, an order confirmation notification maybe sent to the customer and an order placed notification sent to themerchant via a notification component. Inventory may be reserved when apayment processing job starts to avoid over-selling (e.g., merchants maycontrol this behavior from the inventory policy of each variant).Inventory reservation may have a short time span (minutes) and may needto be very fast and scalable to support flash sales (e.g., a discount orpromotion offered for a short time, such as targeting impulse buying).The reservation is released if the payment fails. When the paymentsucceeds, and an order is created, the reservation is converted into along-term inventory commitment allocated to a specific location. Aninventory component may record where variants are stocked, and tracksquantities for variants that have inventory tracking enabled. It maydecouple product variants (a customer facing concept representing thetemplate of a product listing) from inventory items (a merchant facingconcept that represent an item whose quantity and location is managed).An inventory level component may keep track of quantities that areavailable for sale, committed to an order or incoming from an inventorytransfer component (e.g., from a vendor).

The merchant may then review and fulfill (or cancel) the order. A reviewcomponent may implement a business process merchant's use to ensureorders are suitable for fulfillment before actually fulfilling them.Orders may be fraudulent, require verification (e.g., ID checking), havea payment method which requires the merchant to wait to make sure theywill receive their funds, and the like. Risks and recommendations may bepersisted in an order risk model. Order risks may be generated from afraud detection tool, submitted by a third-party through an order riskAPI, and the like. Before proceeding to fulfillment, the merchant mayneed to capture the payment information (e.g., credit card information)or wait to receive it (e.g., via a bank transfer, check, and the like)and mark the order as paid. The merchant may now prepare the productsfor delivery. In embodiments, this business process may be implementedby a fulfillment component. The fulfillment component may group the lineitems of the order into a logical fulfillment unit of work based on aninventory location and fulfillment service. The merchant may review,adjust the unit of work, and trigger the relevant fulfillment services,such as through a manual fulfillment service (e.g., at merchant managedlocations) used when the merchant picks and packs the products in a box,purchase a shipping label and input its tracking number, or just markthe item as fulfilled. A custom fulfillment service may send an email(e.g., a location that doesn't provide an API connection). An APIfulfillment service may trigger a third party, where the third-partyapplication creates a fulfillment record. A legacy fulfillment servicemay trigger a custom API call from the commerce management engine 136 toa third party (e.g., fulfillment by Amazon). A gift card fulfillmentservice may provision (e.g., generating a number) and activate a giftcard. Merchants may use an order printer application to print packingslips. The fulfillment process may be executed when the items are packedin the box and ready for shipping, shipped, tracked, delivered, verifiedas received by the customer, and the like.

If the customer is not satisfied, they may be able to return theproduct(s) to the merchant. The business process merchants may gothrough to “un-sell” an item may be implemented by a return component.Returns may consist of a variety of different actions, such as arestock, where the product that was sold actually comes back into thebusiness and is sellable again; a refund, where the money that wascollected from the customer is partially or fully returned; anaccounting adjustment noting how much money was refunded (e.g.,including if there was any restocking fees, or goods that weren'treturned and remain in the customer's hands); and the like. A return mayrepresent a change to the contract of sale (e.g., the order), and wherethe e-commerce platform 100 may make the merchant aware of complianceissues with respect to legal obligations (e.g., with respect to taxes).In embodiments, the e-commerce platform 100 may enable merchants to keeptrack of changes to the contract of sales over time, such as implementedthrough a sales model component (e.g., an append-only date-based ledgerthat records sale-related events that happened to an item).

FIG. 3 depicts an exemplary block diagram for a synchronization engine300 (or sync engine 300) in communication with commerce managementengine 136 and which is enabled to synchronize product data for each ofone or more storefronts in communication with various different channels(channels 110A-N), where each channel may have different requirementsfor product information. The product data may be stored in product datastorage 306, which may be a component of the commerce management engine136 or the e-commerce platform 100. As shown, synchronization engine 300is a component of e-commerce platform 100, although it may also be aseparate component. Similarly, a channel 110 may be part of the platform100 (e.g. channel 110A) or external to it (e.g. channel 110B).

As used herein, a channel 110 is any way (such as a platform orapplication) to bring or present product information to consumers, and achannel 110 may have sub-channels or sub-components, where productinformation requirements may vary by channel and sub-channels orsub-components. A channel 110 may include functionality for targetingand/or displaying advertisements to users associated with the channeland may have or be associated with an API for synchronization andsharing of product data. A channel 110 may require a copy of amerchant's product catalog (e.g., a list of products and certaininformation for each product). Examples of channels 110 include socialmedia platforms, search platforms, advertising platforms, messagingplatforms, e-commerce platforms, news sites, blogs, and the like, suchas FACEBOOK® (with sub-channels such as FACEBOOK® Commerce, FACEBOOK®Marketing), TWITTER®, INSTAGRAM GOOGLE® (including GOOGLE® ShoppingAds), YAHOO®, and the like.

As used herein, product information may include any information or dataassociated with a product or a set of products, and may include variousproduct data fields such as availability of a product (e.g., in stock,out of stock, an inventory count), a product category (e.g., apparel,electronics), global trade item number (GTIN), universal product code(UPC), manufacturer part number (MPN), brand, gender (e.g., male,female, unisex), condition (e.g., new, used, fair, excellent),manufacture color, color, age group (e.g., 18-24 months), department,size type (men, women, plus sizes), size (e.g., small, medium, 6, 8,10), price, product feedback and reviews, and the like. Each productdata field may have a required format. As used herein, productinformation may include a product catalog. Each channel 110 may have itsown requirements for which product data fields are required.

The synchronization engine 300 is enabled to synchronize appropriateproduct information for each particular merchant or storefront on thee-commerce platform 100 to each of one or more channels 110 (includingsub-channels or channel sub-components) selected by or for theparticular merchant or storefront. The synchronization engine 300 mayuse a synchronization data model 304 (or sync data model 304) inconnection with synchronization, wherein the synchronization data model304 includes information regarding the specifications and requirementsfor each channel 110, such as based on information made available by achannel, templates for a channel, information inferred from an APIassociated with a channel, or based on error data, as described morefully elsewhere herein. For example, a particular channel 110 mayrequire certain product data fields in certain formats or require that acompletely updated product catalog be communicated periodically (e.g.,each month) to the channel 110. A particular channel's 110 requiredproduct data fields may change over time.

In embodiments, the e-commerce platform 100 may store the productinformation (such as associated with a storefront and/or merchant) inthe commerce management engine 136 for example, and the synchronizationengine 300 may be configured to receive (new or updated) productinformation posted by the e-commerce platform 100, e.g., via a webhook,or via a request/response mechanism, such as by an API request to theplatform and a response from the platform. The synchronization engine300 may also correctly format the necessary product information to beshared with or pushed to one or more selected channels 110A-N. Thus, theproduct information may need to be obtained only once by thesynchronization engine 300 and can then be synchronized to multiplechannels, which may reduce load and stress on the e-commerce platform100 and the commerce management engine 136 as compared to having aseparate request for each channel. In embodiments, such as by using aspecified product data field, the e-commerce platform 100 may provide(or the synchronization engine 300 may request), information or dataupdated since the last provision of or request for information. Forexample, the synchronization engine 300 may request prices for a list ofproducts and the commerce management engine 136 may return only thoseprices that have changed since the time of the last request for suchinformation. In embodiments, such as by using a specified product datafield, the platform may provide (or the synchronization engine 300 mayrequest) information or data for a specified window of time. Inembodiments, the platform may return appropriate information and datalimited to changes since the prior similar request based upon therequest from the synchronization engine 300.

The synchronization engine 300 may request data based on a time windowfor which product information (or changes in product information) shouldbe provided. For example, a time window may be from the last timeproduct information was obtained and just the changed information sincethen may be provided. The synchronization engine 300 may also specifyhow frequently an update should be sent or requested from the platform.The synchronization engine 300 may specify what data is to be sent orrequested (e.g., for which products, storefronts, and/or channels).

As used herein, error data may include identified errors fromsynchronization with channels and information regarding how errors areresolved. Error data may also include how long the errors took toresolve. Typically, a channel 110 will provide an error message, such asto the synchronization engine 300, if there is an identified error inany field of the product information as data is shared with or pushed tothe channel 110, such as missing data, an incorrect format, apublication error, and the like. For example, suppose a specific channel110 requires that a product have a description, a price, an image, abarcode type ID (such as GTIN or MPN), and a title with less than 100characters. The specific channel 110 may report whether the productinformation supplied meets these requirements, including whether or notthe data fields are correctly formatted. For example, the specificchannel 110 may report that the product is missing an image, missing atitle, or missing a GTIN. The channel 110 may report that the productdata is not formatted correctly, e.g., a GTIN should not include hyphensor dashes. The channel 110 may also simply report that an error exists.The channel 110 may report that a certain type or types of errors took acertain time to be resolved.

In embodiments, the synchronization engine 300 and/or the platform 100may compile and analyze the error data in various manners, such asaggregating errors across channels, determining how the errors areresolved, determining the timeliness of the resolution of the errors(for example, how long it took to resolve a particular error or type oferror), and the like. For example, information regarding how an error isovercome, e.g., one or more actions previously taken such as by amerchant or automatically by the platform 100 or the synchronizationengine 300, may provide useful intelligence in analyzing, predicting,and resolving subsequent errors.

The synchronization engine 300 may aggregate the error data in variousways in order to help determine product data field requirements for achannel, to provide recommendations for merchants for resolving errorsor preventing errors, and to determine appropriate parameters forsubsequent product information requests. In embodiments, the error datamay be aggregated for each storefront, across a plurality ofstorefronts, the platform, or a subset of the platform, such as byindustry, by geography, by jurisdiction, by storefronts using particularchannels, or the like. For example, the error data corresponding to newproduct requirements for a social media channel for storefront owners inone geographical area may be aggregated and used for providingrecommendations to storefront owners in other geographical areas. Asused herein, the term storefront may also refer to a merchant or userassociated with a storefront.

In embodiments, an analysis by the synchronization engine 300 may resultin a recommendation for a particular storefront for preventing a futureerror on a particular channel 110. The synchronization engine 300 mayprovide a recommendation to the storefront (e.g., to the correspondingmerchant) wherein the recommendation includes a request for updatingproduct information, such as by adding product data to a particularproduct data field. In embodiments, the recommendation may beautomatically implemented, with the required product data fields updatedon the e-commerce platform 100.

With reference to FIG. 4, an exemplary process is shown which uses errordata from a current or previous synchronization of product data to oneor more selected channels to provide recommendations for preventingsynchronization errors for one or more storefronts for one or moreparticular channels. A recommendation may be provided to a merchant userassociated with a product or storefront or may be used by thesynchronization engine 300 to automatically update the productinformation associated with a product.

At a step 410, the synchronization engine 300 receives productinformation for products requiring synchronization and the selectedchannels to which the product information is to be synchronized. Theproduct information may be associated with one or more storefronts. Forexample, a first storefront may select channels A, B, and C formarketing its products 1-10, a second storefront may select channels A,D, and F for marketing its products 1-100, and a third storefront mayselect channels B and G for marketing its products 1-2000.

At a step 420, the synchronization engine 300 acts to convert ortranslate, for each selected channel 110, the product information to atranslated (converted) product format for the selected channel. Thisinvolves selecting and/or formatting the appropriate data needed foreach required product data field of each individual channel. Inembodiments, the synchronization data model 304 may be used by thesynchronization engine 300, wherein the synchronization data modelincludes the required product data fields that correspond to eachsupported channel.

At a step 430, the synchronization engine 300 determines any errorsrelating to the translated product formats, such as by receiving andprocessing errors from the channels. In embodiments, feedback from achannel may include specific types of identified errors while in somecases, feedback from a channel may simply indicate that an error exists,without specifying in particular what the error is. In some embodiments,the synchronization engine 300 has access to error data relating to aprevious synchronization, wherein the error data may include identifiederrors and ways the identified errors were resolved for the previoussynchronization. The error data may include data from one or moredifferent storefronts, various products, and various channels.

At a step 440, the synchronization engine 300 analyzes the currenterrors and/or the error data from previous synchronizations in order todetermine one or more recommendations for one or more storefronts toprevent future synchronization errors. In embodiments, error datagenerated across storefronts can be used to notify a particularstorefront in advance of an action that should be taken to avoid anerror in the future, as for example, when the storefront selects a newchannel and new product information requirements exist that aredifferent than requirements for other selected channels. In anotherexample, a storefront may be informed in advance of impending channelrequirements. For example, if several storefronts in a particulargeographic region have encountered errors for a particular channelnoting that a GTIN is now required for each product, a storefront usingthat channel in a different geographic region may be notified to provideGTIN information for each product, in order to not encounter errors whenthat channel eventually brings the GTIN requirement to the merchant'sgeographic region.

The recommendations may have varying levels of specificity and apply toone or more products of a storefront. In embodiments, a recommendationmay indicate a corresponding product data field for which particularinformation is needed (e.g., Products 1-5 need GTIN); a recommendationmay indicate a rule regarding correct formatting of the product field(e.g., GTIN field includes numbers only with no special characters); arecommendation may indicate specific product information for a missingproduct field (e.g., Products 5-10 should include Women's Apparel forProduct Category); a recommendation may provide the correct formattingfor an incorrectly formatted product field (e.g., Product 7's 14 digitGTIN should be 00012345600012). In order to determine a recommendationfor an error on a particular channel, the synchronization engine 300 mayuse error data from the same channel to determine what the problem mightbe and may use information regarding how similar errors were resolved.For example, a particular channel may have recently added a category asa required product field for a certain group of products and thesynchronization engine 300 may use that knowledge to provide arecommendation that a category is needed to be specified for a productand may provide a suggested category for a particular product. As afurther example, a particular channel may have recently started using a14 digit GTIN rather than a 12 digit GTIN, and a recommendation mayinclude the suggestion that two leading zeros be added to modify a 12digit GTIN to a 14 digit GTIN.

In embodiments, a predictive analytics module 302 as shown in FIG. 3 maybe used to provide recommendations to prevent future errors. Thesynchronization engine 300 may automatically implement recommendationsin a manner such that merchants do not have to provide input. Forexample, if a channel has a new required field for a category of aproduct, the predictive analytics module may use previous error dataacross one or more storefronts to analyze and predict information thatmay be used to pre-populate a category field for various products. Forexample, a television may automatically be provided with a corresponding‘Electronics’ category associated with it when required for a particularchannel. The predictions may have a degree of confidence associated withthem, such that for example, high confidence predictions (e.g.,associated with a first confidence level) are automatically implemented,medium confidence predictions (e.g., associated with a second confidencelevel lower than the first) are provided with suggestions that areflagged for a storefront to review prior to implementation, and lowconfidence predictions (e.g., associated with a third confidence levellower than the first and the second) are not automatically implementedbut communicated to a storefront.

At a step 450, the synchronization engine 300 may send a communicationto one or more of the plurality of storefronts with the recommendation,such as to request product information for newly required product datafields for a particular channel, or to approve of a particularrecommendation prior to implementation. For example, a communication maybe sent to a merchant that a channel has a new requirement for a 14 GTINor a new requirement for multiple images of different sides of aproduct, or the like. In embodiments, the synchronization engine 300 may(automatically) implement a recommendation without communicating therecommendation to the merchant or after approval by the merchant. Forexample, the synchronization engine 300 may provide a suggested categoryfor a product and automatically add the category to the productinformation.

In embodiments, the synchronization data model for a channel 110 may beupdated in real time, such as based on error data, including theidentified errors from synchronizations, successful ways for resolvingidentified errors, and unsuccessful ways of attempting to resolveidentified errors. In embodiments, error data may provide insight intonew product data field requirements for various channels. Thesynchronization data model may also be updated based on reviewing,crawling, or polling channels periodically to identify changes inrequirements. For example, a channel may indicate that it now requires aGTIN for a product where it did not previously have that requirement,and the synchronization engine 300 may provide communication to one ormore storefronts using the channel to provide a recommendation regardingupdating product information to include a GTIN having a specifiedformat.

In embodiments, identified errors may be reported to a storefront, wherea number of errors to be presented to and/or directly addressed by astorefront may be reduced, such as by combining similar errors acrossmultiple channels (e.g., associated with varying degrees or levels ofthe same or similar requirements. For example, if two channels provideerror feedback that GTINs are now required for a particular product(e.g., 12 and 14 digit GTINs required), instead of presenting the errortwice to a storefront, the errors may be consolidated and one error(e.g., associated with the more stringent requirement between the two),may be presented (e.g., the 14-digit GTIN), while possibly noting thatthe two channels require a GTIN to be provided. As another approach,errors may be corrected by revising the product information stored onthe platform. In this manner, a single error may be presented for onechannel but not presented for the other channel. By updating productinformation a single time on the platform, the errors can be addressedfor both channels. In other words, errors may be corrected or addressedthrough revising and/or updating the product information stored on theplatform (i.e., the source data) and not on the channel. In this manner,it may be possible to present an error for one channel, but not presentthe similar error for the other channels, because once the error iscorrected for one channel (e.g., the error with the more stringentrequirement) via the source data it will be corrected for all thechannels.

The synchronization engine 300 may synchronize product information to aplurality of channels, where each channel has respective product datafields required for that channel. Information regarding priorsynchronization errors, types of errors, how an error is overcome, e.g.,one or more actions previously taken such as by a merchant orautomatically by the platform 100 or the synchronization engine 300,along with timing information of resolution, may provide usefulintelligence in analyzing, predicting, and resolving future errors. Forexample, the synchronization engine 300 may estimate a number and/ortype of future synchronization errors based on the error data of one ormore prior synchronizations. The estimated future synchronization errorsmay also be used to determine the timing of a future synchronization.The estimated synchronization errors may also be used as to determinethe timing of and an amount of data requested in a request for productinformation sent to the commerce management engine 136 (or, throughoutthis disclosure, other aspects of the platform 100 or data stores ofinformation) for a future synchronization in order to minimize a load on(or not unduly stress) the commerce management engine 136 (or,throughout this disclosure, other aspects of the platform 100 or datastores of information) in responding to the request.

In embodiments, the synchronization engine 300 may dynamically adjustparameters associated with a request to the commerce management engine136 for product information for a future product synchronization basedon one or more factors in order to reduce or minimize errors that occurin a future synchronization and/or to reduce or minimize a load on, notunduly stress, or to optimize a performance of the commerce managementengine 136. Parameters associated with a request for product informationwhich may be adjusted may include a timing parameter of the request(which relates to when the commerce management engine 136 must respond)and an amount of data requested, such as on a specific product, datafield, storefront, and/or channel basis. Typically, the more data and/orcomputation requested at a specific time, the greater is the burden onthe computing resources of the commerce management engine 136.

In embodiments, the potential factors to be analyzed to determine theparameters of the request may include an estimation of a number or typeof future synchronization errors, a predicted time of resolution oferrors, a determined current load on computing resources of the platform100 or commerce management engine 136, and a predicted additional loadon computing resources of the platform 100 or commerce management engine136 that a request of a specified amount of product data or computationwould cause. Other factors to be considered may include a number ofchannels impacted by future errors, a criticality of the errors, and thelike.

For example, if many products require being synchronized to a particularchannel 110 that has recently implemented a new requirement for productdata for each product, such as a required category, a synchronizationmay be delayed so that the potential errors can be addressed before arequest for this data is made and before a synchronization of thoseproducts is attempted with the particular channel 110 (e.g., the productinformation field for category can be updated or corrected for thoseproducts of a storefront that need to be updated or corrected). This mayreduce pressure or a load on the platform 100 and/or the commercemanagement engine 136 because if the request for product information wasnot delayed, the commerce management engine 136 may not be able toprovide the relevant product information to update the product datafields and the request would have to be repeated. In addition, if therequest required computation, the computations may be started, usingcomputing resources, but unable to be completed, thereby wastingcomputing resources on requested computations which cannot be completedwith the current product information. Also, without the updated productinformation, many synchronization errors would be returned from theparticular channel 110 which would need to be resolved and then the datawould have to be synchronized again. Allowing enough time for updatingproduct data fields at the commerce management engine 136 allows for asynchronization for most of the product data fields to be correct thefirst time and uses fewer computing resources.

With reference to FIG. 5A, an exemplary process 500 is shown which useserror data from one or more prior synchronizations of product data toone or more channels to determine one or more request parameters relatedto requesting updated product information from the commerce managementengine 136 for a future product synchronization. In this manner, futuresynchronization errors may be avoided and an additional load on thee-commerce platform 100 and/or commerce management engine 136 may bereduced (as compared to a synchronization not correcting the errors).

At a step 510, the synchronization engine 300 performs an analysis oferror data from a prior synchronization of product information with oneor more channels 110. The error data may include identified errors fromsynchronization with channels and information regarding how errors areresolved and how long the errors took to be resolved. In embodiments,information regarding how an error is overcome, e.g., one or moreactions previously taken such as by a merchant or automatically by theplatform 100 or the synchronization engine 300, as well as actions thatdid not result in an error being overcome, may provide usefulintelligence in analyzing and resolving future errors and provideinformation regarding how many errors may need to be corrected, whicherrors may automatically be corrected, and how to formulate requests tothe platform 100 to allow for missing product information to be added(such as by allowing for appropriate time).

The synchronization engine 300 may aggregate the error data in variousways in order to help determine product data field requirements for achannel 110, to provide recommendations for merchants for futuresynchronizations, and to determine appropriate parameters for subsequentproduct information requests. As described elsewhere herein, theanalysis may make use of the predictive analytics module 304, and mayaggregate data across one or more storefronts, channels, the entireplatform 100, or a subset of the platform 100.

At a step 520, the synchronization engine 300 formulates one or morerequests to the commerce management engine 136 to report updated productinformation for one or more products, storefronts and/or channels,wherein each request includes at least one request parameter based onthe analysis. Parameters of a request may include how often or over whattime period product data is requested, whether all product informationor just product information changes are to be reported, a set ofspecified times for which the product information or product informationchanges are to be reported (which may be a periodic schedule), and/or aset of one or more specified products or product fields for whichproduct information or product information changes is to be reported,such as on a per product, per storefront, and/or per channel basis.Control of the parameters in a request for product information allowsfor future errors to be minimized in a future product synchronizationand allows for an additional load on the commerce management engine 136or e-commerce platform 100 to be reduced.

For example, if many errors for one or more storefronts are anticipateddue to trends in overall error data or due to implementation of newproduct information fields being required for one or more channels 110,a product data synchronization may be delayed for one or more products(or storefronts or channels) in order to allow time for potential errorsto be reported and addressed prior to requesting the data from thecommerce management engine 136. The synchronization engine 300 may allowless delay for potential errors that may be automatically corrected,such as by correcting the formatting, as compared to anticipated errorsthat require user input. Additionally, the specific data requested maybe reduced in size, such as by requesting only product information thathas changed from a previous synchronization or from a specified set ofone or more products for which the product information is expected to becomplete, or staggering requests based on product, industry, storefront,or channel in order to minimize or reduce an additional load on thecommerce management engine 136.

For example, product information related to products 1-100 may need tobe updated, and the synchronization engine 300 may determine thatproduct information for products 30-60 are likely to have errorsrelating to lack of appropriate images for a particular channel. In sucha case, the synchronization engine 300 may omit products 30-60 from aninitial request for product information to the commerce managementengine 136, and may later present a set of requests for execution atdifferent times to the commerce management engine 136, such as a requestfor products 1-29 and 61-100 at time 1, a request for products 30-40 ata time 2, and a request for products 41-60 at a time 3. A request couldalso vary by product data field for a particular product, such asrequesting a price for each product 1-100 but not images for products30-60. In this manner, there is a reduced load on the commercemanagement engine 136, because fewer computing resources are needed tofulfill a smaller data request than a larger data request. Thecriticality of future errors may also be considered in a formulation ofa request for product information for a future product synchronization.For example, it may be determined that certain product fields are not ascritical as others and a synchronization may not be delayed, evenknowing that synchronization errors may exist. For example, a certainchannel may require a product image, but if a product is selling wellwithout an image, such an error may be disregarded or deprioritized inthe analysis.

In embodiments, an estimated number of future synchronization errors maybe determined, and a future product synchronization may be delayed ifthe estimated number of future errors is above a predeterminedthreshold. For example, product information related to products 1-1000may need to be updated, with an update scheduled for a time T1. With apredetermined threshold set at 50% of the number of products, thesynchronization engine 300 may determine that product information for600 products is likely to have errors relating to lack of a specifiedcategory for the product, which was determined to be a new product datafield for a particular channel. In this example, a timing parameter of arequest may specify that products 1-1000 not be synchronized until adelayed time T2. Alternatively, a timing parameter of a request mayspecify that the 600 products likely to have errors not be synchronizeduntil a delayed time T3. Many other request formulations are alsopossible.

In embodiments, the synchronization engine 300 may determine anestimated number of channels affected by any errors, or determine anumber of errors of a certain type. For example, if a large number of aparticular type of error is determined to exist for one or more channels(e.g. many product images are missing), a synchronization of productinformation with those channels would result in many errors that wouldneed to be addressed. If product images are determined to be critical toa channel, there is no sense requesting product information forsynchronization with that channel or attempting a synchronization untilthe product information is appropriately updated on the e-commerceplatform 100. A predetermined threshold of a number of channelsaffected, or a number of errors per channel, or a number of errors of aparticular type may also be set, which if exceeded, may act to delay afuture synchronization for all channels or an affected channel, or whichmay result in a modification of a request parameter (for example, toinclude only those products for which images have been provided, soother information for those products may be updated).

In embodiments, an analysis by the synchronization engine 300 may resultin a recommendation for a particular storefront for preventing a futureerror on a particular channel 110. The synchronization engine 300 mayprovide a recommendation to the storefront (and the correspondingmerchant) wherein the recommendation includes a request for updatingproduct information, such as by adding product data to a particularproduct data field. For example, an analysis of which other channels maybe affected by missing product images may be performed, wherein thesepotential future errors can be automatically fixed for the otherchannels when the images are provided for one channel. In embodiments,the recommendation may be automatically implemented, with the requiredproduct data fields updated on the e-commerce platform 100. For example,for a product data field that requires a 14 digit GTIN, thesynchronization engine 300 may automatically convert an 11 digit GTIN toa 14 digit GTIN, without delaying a request for subsequent productinformation for a future synchronization.

At a step 530, the synchronization engine 300 may receive the productinformation requested, and/or automatically correct some product datafields, and proceed with a synchronization of product information, forone or more storefronts, with one or more selected channels.

With reference to FIG. 5B, an exemplary process 550 is shown which issimilar in many respects to exemplary process 500, but whereinadditional factors may be considered when formulating a request forproduct information for a future synchronization, such as a determinedcurrent load on one or more computing resources of the commercemanagement engine 136 or platform 100 and/or a determined predictedfuture load on the one or more computing resources of the commercemanagement engine 136 or platform 100 based on a request of a specificamount of data or computation. Process 550 thus uses error data from oneor more prior synchronizations of product data to one or more channelsas well as a determined load to control one or more parameters relatedto requesting updated product information from the commerce managementengine 136 for a future product synchronization. In this manner, a loadon the e-commerce platform 100 and/or commerce management engine 136 maybe minimized, optimized, and/or kept within appropriate bounds.

At a step 560, the synchronization engine 300 performs an analysis oferror data from a prior synchronization of product information with oneor more channels 110, in a similar manner to that described elsewhereherein, possibly in association with the predictive analytics module302. The error data may include identified errors from synchronizationwith channels and information regarding how errors are resolved and howlong it took to resolve the errors.

At a step 570, a current load and/or a predicted future load on one ormore computing resources may be determined, wherein the determined loadcan be used as a factor in formulating a request for additional productdata to the commerce management engine 136. Determining a current loadon computing resources of the platform may include analyzing performancemeasures or metrics for the computing resources associated with theplatform 100 or commerce management engine 136. The computing resourcesmay include network, processing, database, storage, and memoryresources, and one or more of the computing resources may be finite. Avariety of metrics may be used to check a network load, such asthroughput, bandwidth, speed, CPU utilization, average response time,number of (API) requests, request fields or connections, or to otherwisedetermine performance measures associated with one or more computingresources. In embodiments, a load analysis module 308 (as shown in FIG.3) of the synchronization engine 300 may determine a current load on thecommerce management engine 136 or platform 100, although, inembodiments, the load analysis module 308 may be located elsewhere, suchas on or external to the platform 100.

The commerce management engine 136 may be in communication with thesynchronization engine 300 via a network and network performance metricsor measures, such as network load, bandwidth, and speed may be factoredinto a load determination. Network monitoring techniques may monitornetwork access, routers, slow or failing components, firewalls,switches, and server performance, as well as traffic and trafficpatterns.

The commerce management engine 136 may include processing resources anddatabase resources. The availability, response time, processing speed,latency, and throughput of these computing resources may be monitored.Database activity monitoring tools may monitor database events and canbe accomplished by different techniques such as network sniffing readingdatabases audit logs or system tables, or memory scrapping.

A predicted future load may be a predicted future additional load basedon a proposed request of a specified amount of product data and/orcomputation. The predicted future load may be based on historical data,and may be iteratively determined, as an optimized request is beingformulated.

A current load and a predicted additional load may be combined in adetermined load, which may comprise a composite load value that iswithin a specified range and takes into account various differentperformance metrics and/or computing resources. For example, adetermined load may be a value between 1-100, with a higher valueindicating a higher load on the platform 100 or commerce managementengine 136.

At a step 580, the synchronization engine 300, formulates one or morerequests to the commerce management engine 136 to report updated productinformation for one or more products, storefronts and/or channels,wherein a request parameter of each request to the commerce managementengine 136 for product information is based on the estimate ofsynchronization errors and the determined load.

Parameters that may be included in a request may be as describedelsewhere herein and may include a time period over which productinformation or product information changes are to be reported, a set ofspecified times for which the product information or product informationchanges are to be reported (which may be a periodic schedule), and/or aset of one or more specified products for which product information orproduct information changes is to be reported, such as on a product,storefront, or channel basis. Control of the parameters in a request forproduct information allows for errors to be minimized in a futureproduct synchronization and an additional load on the e-commerceplatform 100 to be controlled.

For example, requests to the commerce management engine 136 may bedelayed if a determined load or a composite load value is above apredetermined level. Requests to the commerce management engine 136 maybe limited in amount of data and/or computation requested if adetermined load or a composite load value is above a predeterminedlevel.

In embodiments, an estimated number of future synchronization errors maybe determined, and a future synchronization for one or more products,storefronts, or channels, may be delayed if the estimated number offuture errors is above a predetermined threshold and/or the compositeload value is above a predetermined level.

For example, product information related to products 1-1000 may need tobe updated, with an update scheduled for a time T1. A predeterminedthreshold for a number of future synchronization errors may be set at50%. A predetermined level for a composite load value may be set at 95%.Assume that a number of future synchronization errors is determined tobe 600 (affecting 600 products) with a composite load value of 75%(computed assuming that product information for all 1000 products is tobe requested). In such a case, a request may specify that product datafor the 600 products likely to have errors not be requested from thecommerce management engine 136 until a delayed time T2. A request mayspecify that product data for the 400 products that are not anticipatedto have errors be requested from the commerce management engine 136 atT1. Alternatively, a request may specify that product data for all 1000products be requested from the commerce management engine at T2.

In another example, using the same predetermined threshold andpredetermined level as above, assume that a number of futuresynchronization errors is determined to be 300 (affecting 300 products)with a composite load value of 96%. In this case, a request may specifythat product data for the 700 products that are not anticipated to haveerrors be requested at a time when the composite load value falls below95%. A request may specify that product data for the 300 products thatare anticipated to have errors be requested at a time when both of thefollowing have occurred: a composite load value falls below 95% and adetermined time T3 has passed.

In another example, using the same predetermined threshold andpredetermined level as above, assume that a number of futuresynchronization errors is determined to be 650 (affecting 800 products)with a composite load value of 96%. In this case, a request may specifythat product data for the 200 products that are not anticipated to haveerrors be requested at a time when the composite load value falls below95% and a request may specify that product data for the 800 productsthat are anticipated to have errors be requested at a time when both ofthe following have occurred: a composite load value falls below 95% anda determined time T4 has passed.

In another example, using the same predetermined threshold andpredetermined level as above, assume that a number of futuresynchronization errors is determined to be 250 (affecting 250 products)with a composite load value of 80%. In this case, a request may specifythat product data for all 1000 products occur at a time T1 or a requestmay specify that product data for 750 products that are not anticipatedto have errors be requested at a time T1 and specify that product datafor the 250 products that are anticipated to have errors be requested ata determined time T5 has passed.

In embodiments, a composite factor score may be determined, which maytake into account a number of factors for whether it is desirable torequest product information from the commerce management engine 136. Thecomposite factor score may take into account a number and/or a type offuture synchronization error, a composite load value, a criticality ofthe error, and the like. In embodiments, the composite factor score maybe used to formulate a request for requesting product information fromthe commerce management engine 136, wherein if a composite factor scoreis above a predetermined threshold, a request is delayed and/or anamount of product information and/or computation requested is decreaseduntil a time that the composite factor score indicates favorableconditions.

In embodiments, steps 560 and 570 may be simultaneously performed oreither step may be performed before the other. In embodiments, steps 570and 580 may be iteratively performed, wherein in an initial step 570, aspecified amount of product information in a request is based on a prioror current request, and in subsequent passes, a specified amount ofproduct information in a request is based on a prior formulated request,such that a predicted future load more closely tracks the formulatedrequest.

At a step 590, the synchronization engine 300 may send the request tothe commerce management engine 300, receive the product informationrequested, automatically correct some product data fields, and proceedwith a synchronization of product information, for one or morestorefronts or for one or more selected channels.

With reference to FIG. 5C, an exemplary process 501 is shown which issimilar in some respects to exemplary process 500 in that futuresynchronization errors are estimated, but wherein a futuresynchronization is delayed, for one or more channels, based on whether achannel is affected by the future synchronization errors.

At a step 511, the synchronization engine 300 performs an analysis oferror data from one or more prior synchronizations of productinformation with one or more channels 110, in a similar manner to thatdescribed elsewhere herein, possibly in association with the predictiveanalytics module 302. The error data may include identified errors fromsynchronization with channels and information regarding how errors areresolved and how long it took to resolve the errors.

At a step 521, the future synchronization errors are analyzed, such asby determining a number of future synchronization errors per channel, anumber of a particular type of future synchronization errors perchannel, or simply determining whether or not a channel is affected byany synchronization errors.

At a step 531, a future synchronization may be delayed, for one or moreof the channels, based on whether or not a channel is affected by futuresynchronization errors, based on a number of affected channels exceedinga predetermined threshold, or the like.

In embodiments, the synchronization engine may subsequently proceed witha synchronization of product information, synchronizing productinformation to the plurality of channels, once the futuresynchronization errors are resolved. In embodiments, the productinformation may be synchronized to a particular channel once futuresynchronization errors with respect to that channel are resolved to apredetermined extent or the channel is not affected to a predeterminedextent. In embodiments, the product information may be synchronized tothe plurality of channels if the future synchronization errors areresolved such that the number of channels affected is below apredetermined threshold.

Referring to FIGS. 6 and 7, exemplary user interfaces 600 and 700 may beprovided for a merchant user for reporting purposes and for the merchantuser to view and respond to error data for selected channels of anassociated storefront. Product errors may be provided per product asshown in FIG. 6. In embodiments, such as shown in FIG. 7, the userinterface may consolidate errors across channels. A user interface mayalso consolidate errors across products, storefronts, channels 110,and/or other divisions. Additionally, a summary of errors may beprovided in other formats, with errors grouped by type. For example, allGTIN error data or all UPC errors may be grouped together.

In embodiments, a user interface may allow a merchant user to select oneor more channels for marketing products and the merchant user may bepresented with, for each selected channel, a respective product pagetemplate with the required product data fields shown or highlighted withthe remaining product fields greyed out or removed. The product pagetemplate (and the particular fields that are highlighted/active vs. notrequired/greyed out) may be based on a synchronization data model anderror data, which may be updated in real time as errors are determinedacross channels and the relevant product fields and formats for eachchannel are updated. For example, FIGS. 8 and 9 depict an exemplary userinterface 800. In particular, the user interface may use asynchronization data model that keeps track of product data fields andformats that are required for each channel. For example, all thepossible product data fields for channels 110 supported by thesynchronization data engine may be displayed, such as in FIG. 8. Once aspecific channel 110 (or set of channels 110) is selected for productsynchronization, the user interface may present those product datafields that are required for the selected channel(s), such as shown inFIG. 9. In this manner, a storefront (e.g., a merchant) is provided withonly product data fields that are required for each particular selectedchannel or set of channels.

Additionally, pop-ups on a user interface may alert a merchant user toproduct information fields that need to be filled in or corrected, suchas according to each selected channel. Functionality may be provided tocorrect existing product errors together, such as by applying an addedelement of product information to a product information data field formultiple channels.

In embodiments, a product page template can be also be based on thesynchronization data model, which may be updated in real-time as errorsare determined across channels and the relevant product fields andformats for each channel are updated.

The methods and systems described herein may be deployed in part or inwhole through a machine that executes computer software, program codes,and/or instructions on a processor. The processor may be part of aserver, cloud server, client, network infrastructure, mobile computingplatform, stationary computing platform, or other computing platform. Aprocessor may be any kind of computational or processing device capableof executing program instructions, codes, binary instructions and thelike. The processor may be or include a signal processor, digitalprocessor, embedded processor, microprocessor or any variant such as aco-processor (math co-processor, graphic co-processor, communicationco-processor and the like) and the like that may directly or indirectlyfacilitate execution of program code or program instructions storedthereon. In addition, the processor may enable execution of multipleprograms, threads, and codes. The threads may be executed simultaneouslyto enhance the performance of the processor and to facilitatesimultaneous operations of the application. By way of implementation,methods, program codes, program instructions and the like describedherein may be implemented in one or more thread. The thread may spawnother threads that may have assigned priorities associated with them;the processor may execute these threads based on priority or any otherorder based on instructions provided in the program code. The processormay include memory that stores methods, codes, instructions and programsas described herein and elsewhere. The processor may access a storagemedium through an interface that may store methods, codes, andinstructions as described herein and elsewhere. The storage mediumassociated with the processor for storing methods, programs, codes,program instructions or other type of instructions capable of beingexecuted by the computing or processing device may include but may notbe limited to one or more of a CD-ROM, DVD, memory, hard disk, flashdrive, RAM, ROM, cache and the like.

A processor may include one or more cores that may enhance speed andperformance of a multiprocessor. In embodiments, the process may be adual core processor, quad core processors, other chip-levelmultiprocessor and the like that combine two or more independent cores(called a die).

The methods and systems described herein may be deployed in part or inwhole through a machine that executes computer software on a server,cloud server, client, firewall, gateway, hub, router, or other suchcomputer and/or networking hardware. The software program may beassociated with a server that may include a file server, print server,domain server, internet server, intranet server and other variants suchas secondary server, host server, distributed server and the like. Theserver may include one or more of memories, processors, computerreadable media, storage media, ports (physical and virtual),communication devices, and interfaces capable of accessing otherservers, clients, machines, and devices through a wired or a wirelessmedium, and the like. The methods, programs or codes as described hereinand elsewhere may be executed by the server. In addition, other devicesrequired for execution of methods as described in this application maybe considered as a part of the infrastructure associated with theserver.

The server may provide an interface to other devices including, withoutlimitation, clients, other servers, printers, database servers, printservers, file servers, communication servers, distributed servers andthe like. Additionally, this coupling and/or connection may facilitateremote execution of program across the network. The networking of someor all of these devices may facilitate parallel processing of a programor method at one or more location without deviating from the scope ofthe disclosure. In addition, any of the devices attached to the serverthrough an interface may include at least one storage medium capable ofstoring methods, programs, code and/or instructions. A centralrepository may provide program instructions to be executed on differentdevices. In this implementation, the remote repository may act as astorage medium for program code, instructions, and programs.

The software program may be associated with a client that may include afile client, print client, domain client, internet client, intranetclient and other variants such as secondary client, host client,distributed client and the like. The client may include one or more ofmemories, processors, computer readable media, storage media, ports(physical and virtual), communication devices, and interfaces capable ofaccessing other clients, servers, machines, and devices through a wiredor a wireless medium, and the like. The methods, programs or codes asdescribed herein and elsewhere may be executed by the client. Inaddition, other devices required for execution of methods as describedin this application may be considered as a part of the infrastructureassociated with the client.

The client may provide an interface to other devices including, withoutlimitation, servers, other clients, printers, database servers, printservers, file servers, communication servers, distributed servers andthe like. Additionally, this coupling and/or connection may facilitateremote execution of program across the network. The networking of someor all of these devices may facilitate parallel processing of a programor method at one or more location without deviating from the scope ofthe disclosure. In addition, any of the devices attached to the clientthrough an interface may include at least one storage medium capable ofstoring methods, programs, applications, code and/or instructions. Acentral repository may provide program instructions to be executed ondifferent devices. In this implementation, the remote repository may actas a storage medium for program code, instructions, and programs.

The methods and systems described herein may be deployed in part or inwhole through network infrastructures. The network infrastructure mayinclude elements such as computing devices, servers, routers, hubs,firewalls, clients, personal computers, communication devices, routingdevices and other active and passive devices, modules and/or componentsas known in the art. The computing and/or non-computing device(s)associated with the network infrastructure may include, apart from othercomponents, a storage medium such as flash memory, buffer, stack, RAM,ROM and the like. The processes, methods, program codes, instructionsdescribed herein and elsewhere may be executed by one or more of thenetwork infrastructural elements.

The methods, program codes, and instructions described herein andelsewhere may be implemented in different devices which may operate inwired or wireless networks. Examples of wireless networks include 4thGeneration (4G) networks (e.g. Long Term Evolution (LTE)) or 5thGeneration (5G) networks, as well as non-cellular networks such asWireless Local Area Networks (WLANs). However, the principles describedtherein may equally apply to other types of networks.

The operations, methods, programs codes, and instructions describedherein and elsewhere may be implemented on or through mobile devices.The mobile devices may include navigation devices, cell phones, mobilephones, mobile personal digital assistants, laptops, palmtops, netbooks,pagers, electronic books readers, music players and the like. Thesedevices may include, apart from other components, a storage medium suchas a flash memory, buffer, RAM, ROM and one or more computing devices.The computing devices associated with mobile devices may be enabled toexecute program codes, methods, and instructions stored thereon.Alternatively, the mobile devices may be configured to executeinstructions in collaboration with other devices. The mobile devices maycommunicate with base stations interfaced with servers and configured toexecute program codes. The mobile devices may communicate on a peer topeer network, mesh network, or other communications network. The programcode may be stored on the storage medium associated with the server andexecuted by a computing device embedded within the server. The basestation may include a computing device and a storage medium. The storagedevice may store program codes and instructions executed by thecomputing devices associated with the base station.

The computer software, program codes, and/or instructions may be storedand/or accessed on machine readable media that may include: computercomponents, devices, and recording media that retain digital data usedfor computing for some interval of time; semiconductor storage known asrandom access memory (RAM); mass storage typically for more permanentstorage, such as optical discs, forms of magnetic storage like harddisks, tapes, drums, cards and other types; processor registers, cachememory, volatile memory, non-volatile memory; optical storage such asCD, DVD; removable media such as flash memory (e.g. USB sticks or keys),floppy disks, magnetic tape, paper tape, punch cards, standalone RAMdisks, Zip drives, removable mass storage, off-line, and the like; othercomputer memory such as dynamic memory, static memory, read/writestorage, mutable storage, read only, random access, sequential access,location addressable, file addressable, content addressable, networkattached storage, storage area network, bar codes, magnetic ink, and thelike.

The methods and systems described herein may transform physical and/oror intangible items from one state to another. The methods and systemsdescribed herein may also transform data representing physical and/orintangible items from one state to another, such as from usage data to anormalized usage dataset.

The elements described and depicted herein, including in flow charts andblock diagrams throughout the figures, imply logical boundaries betweenthe elements. However, according to software or hardware engineeringpractices, the depicted elements and the functions thereof may beimplemented on machines through computer executable media having aprocessor capable of executing program instructions stored thereon as amonolithic software structure, as standalone software modules, or asmodules that employ external routines, code, services, and so forth, orany combination of these, and all such implementations may be within thescope of the present disclosure. Examples of such machines may include,but may not be limited to, personal digital assistants, laptops,personal computers, mobile phones, other handheld computing devices,medical equipment, wired or wireless communication devices, transducers,chips, calculators, satellites, tablet PCs, electronic books, gadgets,electronic devices, devices having artificial intelligence, computingdevices, networking equipment, servers, routers and the like.Furthermore, the elements depicted in the flow chart and block diagramsor any other logical component may be implemented on a machine capableof executing program instructions. Thus, while the foregoing drawingsand descriptions set forth functional aspects of the disclosed systems,no particular arrangement of software for implementing these functionalaspects should be inferred from these descriptions unless explicitlystated or otherwise clear from the context. Similarly, it will beappreciated that the various steps identified and described above may bevaried, and that the order of steps may be adapted to particularapplications of the techniques disclosed herein. All such variations andmodifications are intended to fall within the scope of this disclosure.As such, the depiction and/or description of an order for various stepsshould not be understood to require a particular order of execution forthose steps, unless required by a particular application, or explicitlystated or otherwise clear from the context.

The methods and/or processes described above, and steps thereof, may berealized in hardware, software or any combination of hardware andsoftware suitable for a particular application. The hardware may includea general-purpose computer and/or dedicated computing device or specificcomputing device or particular aspect or component of a specificcomputing device. The processes may be realized in one or moremicroprocessors, microcontrollers, embedded microcontrollers,programmable digital signal processors or other programmable device,along with internal and/or external memory. The processes may also, orinstead, be embodied in an application specific integrated circuit, aprogrammable gate array, programmable array logic, or any other deviceor combination of devices that may be configured to process electronicsignals. It will further be appreciated that one or more of theprocesses may be realized as a computer executable code capable of beingexecuted on a machine readable medium.

The computer executable code may be created using a structuredprogramming language such as C, an object oriented programming languagesuch as C++, or any other high-level or low-level programming language(including assembly languages, hardware description languages, anddatabase programming languages and technologies) that may be stored,compiled or interpreted to run on one of the above devices, as well asheterogeneous combinations of processors, processor architectures, orcombinations of different hardware and software, or any other machinecapable of executing program instructions.

Thus, in one aspect, each method described above, and combinationsthereof may be embodied in computer executable code that, when executingon one or more computing devices, performs the steps thereof. In anotheraspect, the methods may be embodied in systems that perform the stepsthereof and may be distributed across devices in a number of ways, orall of the functionality may be integrated into a dedicated, standalonedevice or other hardware. In another aspect, the means for performingthe steps associated with the processes described above may include anyof the hardware and/or software described above. All such permutationsand combinations are intended to fall within the scope of the presentdisclosure.

What is claimed is:
 1. A method comprising: receiving, at a computingsystem, for at least one ecommerce storefront, product information forat least one product and at least one selected marketing channel from aplurality of marketing channels for the at least one product from acommerce management engine from a merchant; converting, by a processorof the computing system, for the at least one ecommerce storefront,product information to a translated product format for the at least oneselected marketing channel based on a channel specific synchronizationdata model at the computing device; determining, at the computingsystem, during a synchronization of product data, error data relating tothe translated product format from the at least one selected channel,the determining including receiving errors from the at least oneselected channel and using a predictive analytics module for predictiveanalysis on the errors to find a way to resolve the errors, wherein theerror data includes at least one of an identified error in thetranslated product format and a corresponding way the identified erroris resolved; providing, from the computing system to a first ecommercestorefront outside of the at least one ecommerce storefront, arecommendation for preventing a future error synchronizing product datawith a particular marketing channel based on the received error data;and automatically implementing, by the computer system, a delay forsynchronization between the first ecommerce storefront and the at leastone selected marketing channel until the future error synchronizingproduct data is addressed.
 2. The method of claim 1, further comprisingconsolidating errors across at least two marketing channels prior to areporting of identified errors to the at least one ecommerce storefront.3. The method of claim 1, wherein the predictive analytics module isused to determine the recommendation and the recommendation iscommunicated to the at least one ecommerce storefront for approval priorto implementation.
 4. The method of claim 1, wherein the predictiveanalytics module is used to determine the recommendation and therecommendation is automatically implemented.
 5. The method of claim 1,wherein the recommendation is based on error data across a group ofecommerce storefronts for a particular marketing channel.
 6. The methodof claim 5, wherein at least one product information field isautomatically updated for the first ecommerce storefront.
 7. The methodof claim 1, wherein converting the product information uses a data modelthat includes product data fields required for each marketing channelsupported by the computing system.
 8. The method of claim 1, wherein theat least one ecommerce storefront is in a first geographic area and thefirst ecommerce storefront is in a second geographic area.
 9. The methodof claim 1, wherein the recommendation is provided with a confidencelevel, the confidence level being used by the first ecommerce storefrontto determine an action based on the recommendation.
 10. A systemcomprising: a processor; and a storage medium configured to store a setof instructions, that, when executed by the processor, cause the systemto: receive product information for at least one product for at leastone ecommerce storefront and at least one selected marketing channelfrom a plurality of marketing channels for the at least one product froma commerce management engine from a commerce management engine from amerchant, convert the product information to a translated product formatfor the at least one selected marketing channel based on a channelspecific synchronization data model at the computing device, determine,during a synchronization of product data, at least one error relating tothe translated product format from the at least one selected marketingchannel by receiving errors from the at least one selected marketingchannel and using a predictive analytics module for predictive analyticson the errors to find a way to resolve the errors, wherein the errordata includes at least one of an identified error in the translatedproduct format and a corresponding way the identified error is resolved;provide from the system to a first ecommerce storefront outside of theat least one ecommerce storefront a recommendation for preventing afuture error synchronizing product data with a particular marketingchannel based on received error data; and automatically implement adelay for a synchronization between the first ecommerce storefront andthe at least one selected marketing channel until the future errorsynchronizing product data is addressed.
 11. The system of claim 10,wherein the predictive analytics module is adapted to generate asuggestion to resolve the at least one error, wherein the suggestion iscommunicated to the at least one ecommerce storefront for approval priorto implementation.
 12. The system of claim 10, wherein determining arecommendation uses the predictive analytics module to generate asuggestion to resolve an error, wherein the suggestion is automaticallyimplemented.
 13. The system of claim 10, wherein determining arecommendation includes an analysis of errors across a group ofecommerce storefronts for a particular marketing channel.
 14. The systemof claim 13, wherein at least one product information field is updatedbased on the analysis of errors for the first ecommerce storefront. 15.A non-transitory computer readable medium for storing instruction code,which, when executed by a processor of a computer system cause thecomputer system to: receive product information for at least one productfor at least one ecommerce storefront and at least one selectedmarketing channel from a plurality of marketing channels for the atleast one product from a commerce management engine from a commercemanagement engine from a merchant, convert the product information to atranslated product format for the at least one selected marketingchannel based on a channel specific synchronization data model at thecomputing device, determine, during a synchronization of product data,at least one error relating to the translated product format from the atleast one selected marketing channel by receiving errors from the atleast one selected marketing channel and using a predictive analyticsmodule for predictive analytics on the errors to find a way to resolvethe errors, wherein the error data includes at least one of anidentified error in the translated product format and a correspondingway the identified error is resolved; provide from the system to a firstecommerce storefront outside of the at least one storefront arecommendation for preventing a future error synchronizing product datawith a particular marketing channel based on received error data; andautomatically implement a delay for a synchronization between the firstecommerce storefront and the at least one selected marketing channeluntil the future error synchronizing product data is addressed.
 16. Thenon-transitory computer readable medium of claim 15, wherein thepredictive analytics module is adapted to generate a suggestion toresolve the at least one error, wherein the suggestion is communicatedto the at least one ecommerce storefront for approval prior toimplementation.
 17. The non-transitory computer readable medium of claim15, wherein determining a recommendation uses the predictive analyticsmodule to generate a suggestion to resolve an error, wherein thesuggestion is automatically implemented.
 18. The non-transitory computerreadable medium of claim 15, wherein determining a recommendationincludes an analysis of errors across a group of ecommerce storefrontsfor a particular marketing channel.
 19. The non-transitory computerreadable medium of claim 18, wherein at least one product informationfield is updated based on the analysis of errors for the first ecommercestorefront.